{
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   "cell_type": "markdown",
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   "source": [
    "# High-Dimensional Time Series Forecasting with Convolutional Neural Networks: Full-Fledged WaveNet\n",
    "\n",
    "**Note**: for a written overview on this topic, check out my two blog posts that walk through the core concepts behind WaveNet - [part 1](https://jeddy92.github.io/JEddy92.github.io/ts_seq2seq_conv/), [part 2](https://jeddy92.github.io/JEddy92.github.io/ts_seq2seq_conv2/). \n",
    "\n",
    "This notebook expands on the [previous notebook in this series](https://github.com/JEddy92/TimeSeries_Seq2Seq/blob/master/notebooks/TS_Seq2Seq_Conv_Intro.ipynb), demonstrating in python/keras code how a **convolutional** sequence-to-sequence neural network modeled after WaveNet can be built for the purpose of high-dimensional time series forecasting. I assume working familiarity with **dilated causal convolutions** (WaveNet's core building block), and recommend referencing the 3rd section of the previous notebook if you need to review the concept.\n",
    "\n",
    "For an introduction to neural network forecasting with an LSTM architecture, check out the [first notebook in this series](https://github.com/JEddy92/TimeSeries_Seq2Seq/blob/master/notebooks/TS_Seq2Seq_Intro.ipynb).   \n",
    "\n",
    "In this notebook I'll be using the daily wikipedia web page traffic dataset again, available [here on Kaggle](https://www.kaggle.com/c/web-traffic-time-series-forecasting/data). The corresponding competition called for forecasting 60 days into the future, which we'll now mirror in this demonstration of a full-fledged model. Once again we'll use all of the series history available in \"train_1.csv\" for the encoding stage of the model. \n",
    "\n",
    "Our goal here is to expand on the previous notebook's simple WaveNet implementation, adding additional architecture components from the [original model](https://arxiv.org/pdf/1609.03499.pdf). In particular, each convolutional block of our network will incorporate **gated activations**, **residual connections**, and **skip connections** in addition to the dilated causal convolutions we saw in the previous notebook. I'll explain how these three new mechanisms work in section 3. Feel free to skip ahead to that section if you're comfortable with the data setup and formatting steps (as in the previous notebooks), and want to get right into the neural network.     \n",
    "\n",
    "Here's a section breakdown of this notebook -- enjoy!\n",
    "\n",
    "**1. Loading and Previewing the Data**   \n",
    "**2. Formatting the Data for Modeling**  \n",
    "**3. Building the Model - Training Architecture**  \n",
    "**4. Building the Model - Inference Loop**  \n",
    "**5. Generating and Plotting Predictions**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Loading and Previewing the Data \n",
    "\n",
    "First thing's first, let's load up the data and get a quick feel for it (reminder that the dataset is available [here](https://www.kaggle.com/c/web-traffic-time-series-forecasting/data)). \n",
    "\n",
    "Note that there are a good number of NaN values in the data that don't disambiguate missing from zero. For the sake of simplicity in this tutorial, we'll naively fill these with 0 later on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Page</th>\n",
       "      <th>2015-07-01</th>\n",
       "      <th>2015-07-02</th>\n",
       "      <th>2015-07-03</th>\n",
       "      <th>2015-07-04</th>\n",
       "      <th>2015-07-05</th>\n",
       "      <th>2015-07-06</th>\n",
       "      <th>2015-07-07</th>\n",
       "      <th>2015-07-08</th>\n",
       "      <th>2015-07-09</th>\n",
       "      <th>...</th>\n",
       "      <th>2016-12-22</th>\n",
       "      <th>2016-12-23</th>\n",
       "      <th>2016-12-24</th>\n",
       "      <th>2016-12-25</th>\n",
       "      <th>2016-12-26</th>\n",
       "      <th>2016-12-27</th>\n",
       "      <th>2016-12-28</th>\n",
       "      <th>2016-12-29</th>\n",
       "      <th>2016-12-30</th>\n",
       "      <th>2016-12-31</th>\n",
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       "      <td>20.0</td>\n",
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       "      <td>19.0</td>\n",
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       "      <td>28.0</td>\n",
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       "      <td>3C_zh.wikipedia.org_all-access_spider</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4minute_zh.wikipedia.org_all-access_spider</td>\n",
       "      <td>35.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>4.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>52_Hz_I_Love_You_zh.wikipedia.org_all-access_s...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "                                                Page  2015-07-01  2015-07-02  \\\n",
       "0            2NE1_zh.wikipedia.org_all-access_spider        18.0        11.0   \n",
       "1             2PM_zh.wikipedia.org_all-access_spider        11.0        14.0   \n",
       "2              3C_zh.wikipedia.org_all-access_spider         1.0         0.0   \n",
       "3         4minute_zh.wikipedia.org_all-access_spider        35.0        13.0   \n",
       "4  52_Hz_I_Love_You_zh.wikipedia.org_all-access_s...         NaN         NaN   \n",
       "\n",
       "   2015-07-03  2015-07-04  2015-07-05  2015-07-06  2015-07-07  2015-07-08  \\\n",
       "0         5.0        13.0        14.0         9.0         9.0        22.0   \n",
       "1        15.0        18.0        11.0        13.0        22.0        11.0   \n",
       "2         1.0         1.0         0.0         4.0         0.0         3.0   \n",
       "3        10.0        94.0         4.0        26.0        14.0         9.0   \n",
       "4         NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "\n",
       "   2015-07-09     ...      2016-12-22  2016-12-23  2016-12-24  2016-12-25  \\\n",
       "0        26.0     ...            32.0        63.0        15.0        26.0   \n",
       "1        10.0     ...            17.0        42.0        28.0        15.0   \n",
       "2         4.0     ...             3.0         1.0         1.0         7.0   \n",
       "3        11.0     ...            32.0        10.0        26.0        27.0   \n",
       "4         NaN     ...            48.0         9.0        25.0        13.0   \n",
       "\n",
       "   2016-12-26  2016-12-27  2016-12-28  2016-12-29  2016-12-30  2016-12-31  \n",
       "0        14.0        20.0        22.0        19.0        18.0        20.0  \n",
       "1         9.0        30.0        52.0        45.0        26.0        20.0  \n",
       "2         4.0         4.0         6.0         3.0         4.0        17.0  \n",
       "3        16.0        11.0        17.0        19.0        10.0        11.0  \n",
       "4         3.0        11.0        27.0        13.0        36.0        10.0  \n",
       "\n",
       "[5 rows x 551 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "\n",
    "df = pd.read_csv('../data/train_1.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 145063 entries, 0 to 145062\n",
      "Columns: 551 entries, Page to 2016-12-31\n",
      "dtypes: float64(550), object(1)\n",
      "memory usage: 609.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data ranges from 2015-07-01 to 2016-12-31\n"
     ]
    }
   ],
   "source": [
    "data_start_date = df.columns[1]\n",
    "data_end_date = df.columns[-1]\n",
    "print('Data ranges from %s to %s' % (data_start_date, data_end_date))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can define a function that lets us visualize some random webpage series as below. For the sake of smoothing out the scale of traffic across different series, we apply a log1p transformation before plotting - i.e. take $\\log(1+x)$ for each value $x$ in a series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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6Oydu376NgYFBtvVnhZmZGcnJyQQHBxMaGoqnp6fa8xo1akTp0qUJDg7m/Pnz9O/fP9O1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\nxuN5hHwOjMdzaK7xYCRumDpqLGLJAjJZo4WOMVlWBZw4MjD1xCbPQIOl2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IUlnVV433Vz\nsXzuuWGtrCHw3LQC8Dcz1nTVozbkwnWXtKKrPYzrLml5qw/plIJjWZoWOhtx09p2LGg/dYH6hRRT\nMVjTxeVLCLgJ+UrP9W1XdCInKXh+5yCCPgdNFZ7Mh4nnWHz9Y+vxl7cvnvZ7Zrznmjm4dlWLDYxY\nARIvaLbiCTMqeV6VO7mfLHSdFHOsmleDtnov3nfdXADAPTfPh8oXUSyY+hnOOC5DV+Tg4RQ5JNIS\n/vmnu/C572+1GT7mpOK06UFgCgZLlVBUpwdYAGEjl3RWkZY/zUG8++o5WNAWwvuvn0e/c9uGWTOS\nCyzoKL1/G1c04MrlTRBZcmz5oo7HXzmO/3nhGDxOHmF/qavE2AQBWBMpCQJPulBYDWpNgCFL5NrR\nFKGk4o1jUQR9AgSWB8dwUFQVz20fQE5ScPnSRluhCEAE+X/1p0tRG3RRI2kzNh8qWdYwvIp9upHS\nHhiz9dR88ne76c9VaQmiAbCcvANgFSQyMjL5IpWJ0IIJTYVDKD2b89r9+M6nNtBMwXg8j+FozvDY\ns7KpmnF9CBCMJErX5kh/AhzLoKXOi699dD2++sC6CneGpAjzyvlvJHqyuCAZLJeDR2uzzya4vsIQ\n1v5h9xCODSTgdvBI5Yq456YFePipQ+gbTWM8kYdD4IijtIXCf33/KK1usmqVvG4BPMfQ/Pt3/5d0\nmrdaOwAk9dhjAK/dR6NYPqfENo3Fcwh4RFsTYgA40h9HNFnAD58+hOPDKfzTfWuosWY8LeFQXxyx\nVAHXrGrGVSua8ccWc1uC+Of7177Vh3ExzqNQTwNg3bK+HRuXN1HfNoAwVmsW1mHzgTF4nAKVCJRX\nTlWKM5UKKBaAZTWktIYJorQKpfHKKTBYLMvgI+9abCvk8bg4qLyMouF/xRv6Gc0C3EI+B/rHM3Qx\n+but/bj7WgLQcgVlWoE7OW47wPKJXkiKhcGSKi9SzVi/uAFzmoOoDbpw3SUtuO6SFqiahp8+d9QA\nXzNLF9WGHIBhqr6oI4SqgBMDjA4VDHZ1x/Dkpl5cuqAWN65uo9tsqvHQ844ZJrI+t2Dr+UifP42A\nJaHlGPSiE0PRWegfz2D+bBExhgfD8gBratY4W6q8UtQEnHA5eOQlBU6RQ38khV9dFUTBwQIDKvYM\npXCpl0OmewS/3zFA/06OkDSexgmoysgYF0oMlsaUnrHytkuKrkIUS9dyVpMPTpHH7CY/XA4OT2/t\ng6JqWNgWxitRDSxYaNCQzBJgFEsTIDoeJ78rqoYtB0axpLOKertNFSdLEb5d4oJksKaLzsYAeoZT\n2HZoDPVhN9Z21UPkWfSOpLHrSAQL24lXjNXJ2+sSaB80K4PFMgyCXgfiaWnKsmWANEkGgI4GH97o\njlKDyN++fgKf/a8tFa0ezMbHWw6MYTyeR89QytZk9ZFnjwCYLIA9mzGei57SZHUxLsZbGVqF1NnJ\ngmEYG7gy41qDEc1LCrVOKO85eC7CykCZjM6k79B04JkxWCYOsQISTdeg8DLkgkb9iMi+StsN+xw4\nOlAyYba288kZ1+vE0Sh+8cMddKyzRvn98Ys+G4OVV6dnLliGmcRQcSyLb31yAx64ddG0f2sNazWj\neS1FRofKcHhx5yAcIod7blpgS+M31XgRNcyQo0nSBinoEW0dAFSdgA1YzDqE5qN0DvF7OfAsD01l\nAEbDLevb8am7lk3qHlEeDMOgzfDQWzmvBqmchMF6EdEQT9KQrIZoiEcomcHjrxynVih+haTqxoNN\nqEpLcIqGyJ1zQEXpGTPT2lYNFsOWrpHDAFsCz2HZ7Br0DBGgOb8tRFKEhkfW5oMkvT6RIfcxnpRR\nkBXs7YkhlStS1ni6cPFOSKo84+f5fI0zAlgvvvgibrvtNtx444348pe/fLaO6ZxGZ5MfmXwRh/sT\nuGR+LViWQXOtFy/sGkQyK9tKuT/9nuV48EOrUeV30h5t5dV2IZ8DccOxeaqIJklT5atXNiOTL6LP\n8O4w/W8O9k42TCvvWP/avmHqoGwa0HEsU7E9ztmItJzBl7Y+hH3Rg+dk+xfjYpztOB0Ga6por/fj\n9itm4f5buqhepOMcLmbMsAIZeQrB+nQarFNhsCoxPaquQRVkaKoOpajREnsrmFs5r5b+vLA9VJYi\nVOB2CnjxqSOIjWdRlCcfT3mK0Cd4DQ0WASmSMrO+euXhEDmaYptJaJhcJOB3clAZFoORLOY0B2zF\nCADQbBhe/vW3X8eJkRTCftK9wpoiVHUVTNnUqqZDONyfAM8xEEUGPMMBOguG1bC2q37GesM5zUGj\njVWVTVi+bkk1bljbhGiQRzBfwN+/ezG+/rH15JyKWUgMj8MIwZdX4Szq0DUNDXsG4MyW7p2pwdIs\nAN7eY7B0L69Y1gifW0BHgx/z24IAdKgKeZ7yEgFtiQyZM3Wdwev7RvHstn6E/Q7admy6MC0uzCrT\nt2ucdopwYGAAX/jCF/DYY4+hqqoKH/jAB/Dyyy/jiiuuOJvHd9aj01IyftUKkjasDblIWw6vSB2a\nAdCWMWG/A31jabAMQ3VXZlQHnNjbE6MNiCtFPCUh6BPJSwFg//EYAh5i2Odx8hibyEEuqhAFDpqu\no38sPcntdvOBMUhFDQLPYk1XPZ7c1IvmGu8kY8azFXklD03XkCmeH+2ALsbFOFlUYnbOJG5a205/\nfugj6ya9++cibAzWVCnCMlNRXdfppDiUGUZ34gRmB6f3BbIyWOXbVnjD/DNfhOCZzGCtW1SPnxgM\nem3Ijf6xUvuwnClyN/CFWsEItBwA+0QvelP9KGoKWIaFoqtQNAU8e24VLJoNPJCfBWi0Tc68lslF\nUs01XtvvPMca5qsK7n/oJWiaDmfHINQAub7r69fh9dFN8Lg4JEDSz5qugmN5dNQHMZiSaBuymcTN\n69px1YomJDIyGIuwfNXCMCL5GHqDPBgAjVoKAk/MoqvkBOIOL6JeBxADwkkV0V/9Ao2/fwMbG0Q8\n6tGwoK2KVslaPdWs991agDG3JYh///jl9HeW0wGdga4zUHQVuUIRqVwBLIBqvxs//f1RAMBdV82e\nEQg2TVrzSgEe4e1buHPaDNbvf/97vOMd70B9fT0EQcC//du/YenSyc1gz7dorPbg6hXN+Nz7V1Lz\nMtPW4GO3La5I05qsVdjvmFRBd+XyZmQLCn5mPECVYiItIWSIZdvqfNhxJEJbcFy2pAGqpqN/PIO8\npGD30Si++KMdtr+/88pOqKqOrQfHEPSKWGD0bTqX6UFTJ1Gul7gYF+N8DY0CjrOf1g4bHkHnOhRd\nBcuwEFmBupyXh1YGJK1AYTwXxU8PP2b/fiGPnr/5JHKHD9HPpmKwNF2DagFYpoeRFfiJAof/+xeX\n4Mv3rkbY50AmX4RkuJsTBqtURagqk+9FufO2T/RSpsInEAAjTXHuZzOsx0GfHUUB7yApNGsjczPM\nucBs3bJkVhX1sgv5SN/MoFcAwEDXgbsX3ooOfyv8PjJvOAQOiq6CZzl4nQ64nMwpPVcCzyLgdZB0\nnoXBKigSiqqClJfcLyVO0pE+t4AaOYFYGEjNHSLn9bNXEX/2dyiG/WgfkXFDcxH3vbPUSL20UFFs\n9306dlSDBl1nwIIBoOP1/aO09++n370CH7l1ETYsbbBVzE4XXoFc3/Q0BQ9vhzjtJUJfXx8EQcCH\nP/xhjIyMYOPGjfjkJz8547+vqvKe/EtnGDU1ldNnn3zvStvvN9X4cP36WVMi67bGAIBBNFR7J22z\npsaH1buHsNUs62aA6mqv7aVJ5WS0NwZQU+PDbVfNwTce3YVvP0F6Gr7zitl4dtsANh0cw0s7BzHb\nsmoKeh1IZCRcsbIVTqeIR545hK7Oaqxe1oxF2wdw7dr2Kc/xTCMvEADo9gintI9zdTwXo3JcvN6l\nYDmjz56LP6fX5Vxu2zHEgWc5ODgRvMhU3JcrRoZtXiD/Lyt2MJJX8ra/y49koCYScGQT9HOeY+Fw\nTL5OnrQIhSfMmSjwqK8ljL/Dxdm+a/4cy5LvMgKPcNgNSVZRHfZglDd8lwIuVJWxPu6oXfNWH6oC\nDE12yO1HUk7BE+BR4/HZ9nW2w5MqHYc5zk3wgMfrwmf+bBXWLGmsCH5+/uA74BB5QNfBcSySGQmy\nquPWjbPhcvD43vYDePFYH9YtaUBNjQ9elxsMS1Jxt145By/F98IlOuB1uaCltdM+P5+HpwoqwcVA\nAIO8gxyvGwpqanyocwE+NY9cXQCZ6lJWpOU9d+Hokmpo//AdXKEPYnZHKXNjGqE63TygqJh3ooB4\ngIPbO917pQM6C57jIDM6ntnaD85NAGx9bRAL2gK48fLOGZ/bHLEF2AvIQv5tPcadNsBSVRU7duzA\nI488ArfbjQceeABPPPEEbrvtthn9fSyWqSiAPFtRU+M7o7Yt1nCYfeNcfMVtru+qowBL14GBoQQt\nVdZ1HZFEHl3tYUQiaSxuC+Kuq+bg0RdIvz03x6C5xouXdg4CALoN8ehlixsABnh97wgEaLhyaQMW\ntwfhcvBIJXL41J2ELTxb51ge0TTxN0ml8zPex9m85hfj5HHxettDMvq6ZbKFc3ZdzvU1T2fz4BgO\nPCMglc1V3FfSqM7KF2REImkUysrZs8U8xsdTFBxIY0bHiUQGnLG9YlFFsahO2n4ilaMM1thICoEq\nFxgwSGcqjwOCoWP66k+2408uJ2lJXVWpuml8LG3TOgFAOmM/Xqum3cWSdNDw+ATgFc/p9TavIwAk\nU+T8CtkCdJbFvEY/otHMlH9bLpy4ZkUTMqk8MgByeQl+t4h71s1HJJIGo3KQFIk2M356pEBSabIG\nuVg87fOrDTsxZPwcS6aQkrOkohBAYiQCLpJGdYEwWfFqDjqj4UirAx1Vs+C86gYUx/dgsNUBx5Yd\nGBuKgRXJ9TZZq2Q6h2ImjRs2pyDxDOLrs4i4Kh8rw2qAzoBjODCMjkRaQkuLE1EAiYk8FPHUkmWM\nSsDvifEhzHPPP8m3z32wLHNapNBppwirq6uxdu1ahMNhOJ1OXHPNNdi7d+/pbu68DtP7aap2MgvL\nyms/+m+v4A+7yaOfLSiQixrCFv2Gqf0yBZPrF9t7pHU2+fHBmxbg+kta8IEb51OhZXXAddq95k41\nKjWPvRgX43yOSuLvt1uoOjGhFDh+xhqs8vPVdA2SRRysF4l2RldKGhpdR0URlqqrpRSh4fvFsdyU\nurawn4xrPcMpfP3nxOjTajSqVEwR2j+zamx8opkiPPfiZr1MwF2MRKDLsq3R8+mEqmtgGY5eAwcn\nQlLl0jXRVAgsD57loeinX5l6x8aSzq6gSihqClSOgSJwUDMECFUXSAHViI88K7+7LADu3e8CwzBw\ncg4caXMCkoTc4VIxk2rRYDl7yDymctN3CWhr8CDodoNjWTTVuDGvJYgF7SQbczrG1CInwi/6EM2X\nfCMlVcaeyH4MZ6Z2gD/f4rQB1pVXXonXXnsNqVQKqqri1VdfRVfX+euoeiZRH3bB7eBtAnlrsCyD\nf/3wWrzX8IIBiI3CSCyLj//7qwCAkMWgk+dYfOPjl+Fv714BgJhmWs35zJYOTTXeGeesz3acjmnj\nxTh3oWoqDk8ce6sP47yOC+GZVTWFACxWoL5Q5aFpdmBVCfyYJo2fe+1L2Ny/2dh4abGka3pFkTvR\nYJGJVDJsKTiGnXKhZRq0Wtv5OEWOCqYrabCs94cBg4CjNK6aGqw3o3rMqi8V+kdx4rOfRnbfXjD8\nmRUOqbpqa3AscqINMCq6Ao4lVg0zbW1UKXiLCaiklGwuJBcP1chANPIFqCyPhKN0/0xA6+AcGK0m\n847UTyrarQUTqqbAc4xkVuJ+floNlscB1HlcYBkWc1r8+Mx7V6AqQMA3y5ze9ax2hRHNx+jvPz30\nGL637yf4zp4fTmlhcr7FaQOspUuX4t5778Xdd9+Nd7zjHWhsbMTtt99+No/tvAm3U8C3/moDFs+q\nmvI71UHXpJ5hpu8JgEkVSH63SJvNBjwi/uMTl+OmtW0ASGXOWx1ns+T9Ypx5PNP7Av7jje/jWLzn\n5F/+I40LhsFiOYisMAMfrKnPN6fkoWoqknIaWwdJ5wcbgwVMKXIHo0MQOUh58n2e4acEWALP4l8/\nvBb/+MFL8Mk7l8Ahcmiq8YJhTQar9He5QwchDQ3ZbBo4lkPQCrBMBus0rRpOJTSUrpt32wH685ky\nWOUVkA5OtBUsqJoK3mSwzsDnySpAl1SZMp6yky8xWC4GvNdtYys9hoDcyTsgCyy0UADSIAFSuq6j\nLlZEV3ceiqbA00cqRMWiPi0YnPvacax58ig4hpvUtskKNk8lqpxViBVKFkYTBZLqjksJvDa89bS2\n+WbHGdXB3nHHHbjjjjvO1rG87cNT5mD8+j5CZd60to16jEwVLMtQgFZ7HnQFn251fDHe/IjkiRtz\nXEq+xUdy/sbZtml4K0LRFPAnYbDKgVVFgFXMUxaLM3oo2lOEUzBYRuWXw8lTBotl2WkNH6uN8WpJ\nZzW+81cbwDAM3baqlMDU2CM/hrOjA9pV7fQzjmERcJSqoUspwjevipDVdLiPlJzPTZuG043JAMsB\nWS1C0zViQ2HcY57hoUOHqqm0WvNUwu6ZJqNoAKCCg4OaJgBLzqYhl+FFK4MFAEpdGPIgOX9FV7Hs\nSA7zeyX0tQxCyBKg6yhqyBrPgJJIYOz//Rj1H/ggOB+Z1/yRDHxJGSzDWoxKTYB1ugxWCDvGdtPr\nmVfyWFazGIOZYfQke3Fly2Wntd03M/7onNzPZVhbRDAA+sbSWNgewu1XdM7I+2NBWwizmwOY1zrZ\nf+XNjgsh3XIhRXlPuIsxOcwB/VzYNLxZoeoaWJaDyAnTaLDsvQgrpwjzyCnEmJgziol0a4pQr8xg\nmdsiAMvQYDFTa7DKw9wmy0xmsDSpAE2WbQwWz/AQLGDEBFhvRoqQG4vBl1HhKmhgLX5dZ5oiLGqK\n7ZwcnAgdOgVARQMwuAUCTHOn2RLGCrCsDFbByULNkBTheHwIMZRMq3mWh4MjAnK3YeYp1QYhj41C\nk2VomgpfllyLpqeJXVCkSoRD1lE09GK5gweQfWM3svtLmmt3WoZQUMDpjG1xzjLsadub1LiqoUOn\nOqyckoebd8HNu94Ujd7ZiIsAqyy2je7CU8efO62/tQrQFxnpxIYqz1RfnxRBrwOfe9/K86Kh8kWA\ndX4FBVhnoNm40ONCYF1VvcRgTZ0itPcirJS+yysFymDxxn/r6skZLHNbTpcASTI1WNz/Z++94yS5\nynP/b8WOk9PObN6VtLsoayWEgEsGCTC++HevzQVsbF9jY2xsA+aCbcBgMNFgwDYm2yRjMkgIJIEQ\nyjlv0kZtmhw6x0q/P06dCj09szO7kthd7fv57Gd6u6u7q6qrznnO8z7v8y672EVpo8Hymk08y4qN\nKXoLcxP4YD0FKcKRL1zN/71mllQjXuX4hKQIlTjAAoI0oe0JgCXBZKm5cLXiYiEXFIaq03SaNGWr\noYQapAidapVmRKuVNTIB4JFmnuWBLHge9f37cDyXjoqDrYFea+IpClPDGZEi9D+/OSGaTNf2C7mC\nZ9ukquJaSdfd2NxxvOlBgBUZ0TFgojIJ+ADLSImiAfvJZzifiHhaAqy5G67Dmp5u+9oj0zu4d/Kh\ntq8dK5JmOFi8eKuoFFw/fGp6eJwBWCdXyInoVAYPT3acDtes48oqwoUZLClyX0wnWbVrVC3BjIQp\nwghIWoDBkmmsRFIPNFjaMVKE7aKdyN1tNvFsO2bw2SqAzhhpFJSnlKHosOLT4IkyWLavsZJh+gBL\nHpN4XaMjMNM8ToDl/+5JPUnTsYLrpWYqeM0mTr2O12jQNMTx9SS6YxWbmqqR1BLMrO1B6+hg7vqf\nYdsW2ZrLtrNSWGmTan+WetpAAdyauJ6ak0L6Uj8gAJaVmwu6LqbrbkwjqCkanuNQuu/eWIp6KbEi\nMwTAeGUSy7GwXZuUnvJTrmcYrJMynEqFme99h9J97UVytmsdd4NJRVG44twh/uQ3n8EFG/v50B9f\nzhXnrjj2G0/COCNyP7miXdPdMxGP00HkbntCj7O4Bqu9k/sbtryGf3z23wE+wPJTT0GKMDLBuYtU\nEWoSYNVPnMGSNg2e44DjCAaLhRksUzNJaIknPUUYBXkdzVaAdWIMluVaLSlCoXWSujLHZ7gCBss6\nXgbLZ430lK/BEtdL1a+nyufGMZoODZ/BWtO5isH0QOwzUnqKChY9L72S6o7tlB/bg+rBXJfOzldf\nwu6XbsGW0pdiidmf/oTabtEmqXH0CG6jgT0bVvql6g6On0qUAKt03z2Mf+Hfmfr2t5Z1fAnNpC/Z\nw3hlMriW07pgsE6VHoVPbrOnkzDces3/2745s+06J+RN8sevCq0qlpMePNnidEi3nE6h+l4yp3p3\n+SczTg8GS5T4m6pBqVnmkentXDhwXnybltSg/JvSk/Qku0lqSWpWCLDapQhZsNmz4zNYRosGa5kA\ny//oAGBZTf+vFbNH0HwgsjI7zGh5HF3VSepPAcBqhJ8/kPOrJXv7sOdm4UQZLG9+FSGEAEu0ytHJ\n+gCr3Dy+fq9ybE7rKUqRnrFlH2BNTh3EtDwGe1Zy1drLuGrdi+d9RtpIUbWrpM6+GIDSNtFhpJRW\nMQazuJ6LMSUA54Yf3ctsXui59L4+7NlZrKlJmrMzwed11BXG/PSu4zqoqhq0aCrcfBO9r/gNjN5j\nN3uWMZwZYrwySU0CLCNFUk88JUUQT0Q87RgsCawWAliWa51Q6ezpEu5pwAacTnGGwTp2nA4MluNP\nvpLd+OK2r7fZJg4k5V/V17uk9CRVuxZMSqYboJ3gM6RNw5HSGDtmd8c+W1U0Ekkdx/GwLcFCSEH9\nso/HB1iu77LfmiKUGp23XPRG/vDc15HSkyS0J38CdSohIBmYEYDA6BO6WUU/0SrChVOEric0Srqq\nkdaFb9RxM1hSL6cnaTrNQLOX97OAhbFDmJbH+sFzeNXGqzA0A0OLs3NpPUXVqmEMCL1TZbsAQ6WM\nhuM64p/PYKXyoVg+sXqNONZikcZMKLfJNkPRvuO5aKhUd+5ATYudsqYml3WMw5kVTFWnKVviu2WK\n8IzI/SSNAGA12v9AlmufERITHcTPTOgnQ8jJ0zpzbS4Yp4NNgzSpfOHq53LRwPniuZYFX6DBajEc\nlSA8baSo2XWqVg1d0UgiJtWoBsvzPFDgxsM38/09V4efHUkRAtTrttBgLXMccH3dl6wijDFY0RSh\nLwbvNDu4dOgiwHc+f5JF7k4lBDV90zVsU0PNiIzDE5EijKY+oylC6SWlqzqqopIx0setwZJEQFpP\nxTRYuYwPqMenUYBEZmEdcNpIU7VraF1dKKZJfY/QVZXSKrZnC2f/ZNizcfjP/oL0uefR/ULBhjnF\nAo3xUUppFU/XSNfdQPvneA5dZQd7bo7OZwtLhcbRo1T37GapMZDqw/acwL1dpgil7cXJHk8bgDX5\n9a8ye+01gVDPbSyUIrQXdax9usSZFOHJFXIybZ4i1PhTHVEH6lNh4F0ohCeSjqmZbOoRzXHl6j3Y\npoWpk+ySBOFpPUXFqlKza6T0FKYrno9XEQoGy3btGGh3fYCX9E2QG3X7uFKEEmBJHyy34QOsFgar\nVYMFkHySNFjVXTuZ+I8vi/2JMFi67dJMGqgJUVWnaE+EyD0EaQmfNWq2ACwQVZPl4xa5h6nhqAbL\nMlTUjg6MCaGN0tILG1dLBktRFIxBISrPZ1UsQxQ2OJ6LkwgBVubc81j1tneQ3CCuTbtYpLn/AOP9\nBm42TarmBMyp4zoMTYvfseOyZwIw/e3/4ujHP4JrLc2JvS8l0olHSqJlj6giTODhBVWTJ3M8bQBW\n+eEHqe7YfswUoe3aAY37dA6pk3i6n4eTJeRgeqpoD57qiF6np/I1G22zIh23yy0ppFYnd/lXAqwO\nM0vZKlO1a6SMJKZ/OuI+WELk3qo5jaYIAb77lfvRqsllpwjl9vMYLNuK+ZRp6vx0XEJ/clJA5Uce\npnjn7bj1euATJaFeM6mhJgXTdOIpQnsBBqsRLN51n23sMLMx/dRyQv7uaSON67lYrk1SEyBR6+8n\nOSlc0LXkwsbVaT0VavW6hf/iwRHfgNRPEXoRgKUm/PY3ySSKYdA4+DhuLsd4v4HXkSFRs6g7jQCc\n9c02UEyT5Lr1qOlQkxwFuItFX9IHWOXRYH9biwZO5nhaACzXauIUi9j5XACsvEVShHCGuTmjwTq5\nwj7DYC0azmkCsGzXQfPTZh2mmJAqLRPwQhos2VS3w+yg2CxRs+uk9TSGr8GKObm7gsFyPCemOZU2\nDZLBAtAmO5fPYLmSwfJF7s1oinC+Biv/q1+y501/JDyV9GTg4XWiYc1Mc+RjH8YuFQNvKLtQCFKE\nj68R4KNpqCiGOOYTAVieJ1rKGG18sFpThCB8qY6XwZKu+ykt9E2U3lZaXy+m78KuphYBWEYKy7WE\nNMZ3fz84IvbX8Rwcz8GLpAhlKIqC1tVFZZswGx0fMFD6e0lMFcDzqDl1HM+hd7pGYs1aFE1D7+kJ\n3h9N0S4WvcluFJSAwRIavbjtxckcTwuAZc8JJG/n85EqwvbuufIGeLrrsM6kCE+ukBPcGYDVPqJa\nwVP5mnU8JwBKWUMaUbYALDfOXLWK3DvNDmp2nUKjSEpPorcDWAGDFdecyirGvsEML3j5OXR2J1Fm\nMiegwZIi9/YpQukmPvVf3wDHwalVSempEwJYhdtvpTkhNDvV3bup7d1D49AhnLI4j/mbb2L2xz8C\n4PE1AsSmS42gRY6iHv+06HouHl4sRWhqJqZqkK8X5qcIzexxi9wl85gyQoAl3eHpDyv11GMwWCBa\nKw285rWY52/m6JCJgoLjCg2WpmkcvWwDN7xiTey9MKy0uwAAIABJREFUemenICwMg+keHWX9WrRK\nje6SQ82q4zkO3bM1kuvWie1jAGtpDFa0V6WpGsKJXj/DYJ00Ud39GMU7bgPE6kl6drj1xRksy7Hw\njrNy5nQIOUmdym1HTqeQk+qpMKj8OuK0SRG6TpA+ypoyRRifjEIH9/giSIrcO00hap6sTpPWUxht\nU4QRBsubz2ApisKWC4fZuGUA8gkWsORaMOYxWFZYRei6Dn3JHl6+7iX8zjmvDsAQCOlGWk9St+vH\n9Tt6rsvk1/6Twi2/AsD2LQTsQiFgsPK/uCF4PDYiAIajhMxV9DwtN6wAQIUpQlVRGc6uYLQ8HrCF\nUQarZtePy37F8VwUlCAtCNDjgxFloD/8/vSxAVbNrpI+ZxNdb/0jHE0hqSeYreeYq+cwNJOJ55/L\n6GCc2dM6xXd5q4dxVQV9w3oARqYt7h6/j+SO/ei2R+rsTeKYowDLT9HapeIxwVa/r8NK+yapyUjK\n9WSP0xJgObUa+Ue3Ubj1Fo7+00eZ+9m1wWvShXZBkbu/Kpj93OeZ+ubX/W0bTzuwdYbBOrkiYLDc\nMwCrXcRShJy616zjhY1/M7qYUFpTSFHmKiruDxmsbLBdV6ITTfpgxZy0Qw1WVHPqem6s8fDQcCd4\nClSWV1nnBhosyWA12DH0PA51nweOsH74jQ0vg517OPievwnfV6uR1JN4eMc1gbrVKngedqkIgDUj\nAJZTLOC2SUs1Uzr7rrqQm148EgFYx5+9aGWoZKzyfb6C130wLJ3VK3a8kGEpEXimaWEKT4rCecbZ\nwXOLMVgp//tDawVxsVy59kUCaKPwsjUvEL0xW0Tleqdo0m2vHQHAHBmBdIqV0xY3PP5LLrh3gnx/\nmuzFlwBg9ISsmusDrNFP/zMTX/3KoscpFw5XDF8GcCZF+OuO6s4d7Hjv+5n+3rfnvdYcF32UnDYi\nd5k/B7DHxmgcOYzbaLDvz9/E3E9/8uTu9EkWp0NF1ukU9hmR+6LhtLAwp1IUGkX+/KZ38tjcXuHk\n7k8omu+VNL+KMM7WSUZL6pk6E2FZ/nBmBbqfrmMBBguiaUc3AGpAIHb3rOVNFWEVodRgWeRSK8in\nhsB2UPzvaI6Nxt7XHB+jc0KAo+WkCT3bxnPdgA2ReiIrxmDNB1iqolI4fy25DjWoHoy1FFpmyAW6\n0QKwRrLDVOwqM3XRuFiK+4NChuMwG3U8J2gMLqPfF4Xbpk4tJb5jMQ2WbNdTaPi9C31gvLZzNe+9\n/B285/K/Zk3nKkzVnNdZQPMBlrVaVB8mNBP9nLNYM96kt+jQUXU5fOFIkHJNbd6CuXKV+J5KGbuQ\np3HoIPX9+xY9zt/Y8DJ+Y/3LeMX6l/jfcyZF+GuNzHnnY3R14tZqDL7ud2OvWdNT4kGzOY+Vyt97\nF8+/X1xobqUqLoBRMQAU77rzyd/xkygWa5Xzg70/4WP3fWbe84cOzAYr1jPxxIb0PlqoAfDTPaJV\nbqcawNqdExPM7WP34LohwAKRJlyoilA+dtposGQMZ4bQZIowJnIXPlgyZWUHQMvm3PvGmfvZtbj1\negCwWC7AcuMaLK/ZwFZNbNVEsZ3ARV4CoNTmLQBMfOkLdH/xBxiWuyyAdeBd7+DQ+9+DW10AYOXm\nAoseACWRYHzrelRFxVB1LNcOGaxl9syLxsIMlmB5vrL9m0CYmgsYLOs4GCxPpJMTbRgs27X58W+u\n5MArL17UpmFFZghN0ThUPALEPdWyZiYwvDU1A9dzY6nMxOq1aNkOaqtE+x1DM0hdcAHZmsu5+8W5\nLg+G12L6nE2sff8HUXQdp1ymumunOI5iEWtuLqbNi6Zp13et5eXrXxJc3wGD9RQ0BD/ROC0BlppI\nsOb1ryWxdh1dz3vBgtt5Td/Sv1Kh9MB9TH/pi1y0pyaaozYa2IUCjaOHgbCEFaCy7VEe/7t3BcLN\n0zFadR7RuOnIbRwujcYmspnJMl/77F3ce8vjT9k+Pp3iDIO1eLgtoONkDjufxy7kg//LFGCHkfXb\nqEQAlpGdx264kUnuy9u/EUzOsnFyhy+OBxjODIbNnp1WkbsSCNwlMFAbFpsenGDmh9+neO/dxw+w\nHF9i4AMsp2nhqAa2aoDtoPrtga2paRLr1jP4ut+Lvf+cw43AsPJY4bkuTiFPc2wMpyrOhVMq4TnC\n5BKgORpnylb99bs49PzNKCgYqoHtWvCkpghHWJEeZFPPWbzp/N9nfZcQjEsGq7VSdCnh+GDcVEOA\nJQsjLNcibzpUztuw6GeYmsGq7AgHi2Kea7X8CLbzRftRiULH1kvZ8Kl/oWEq/jYmXRduxVXg4t01\nbA3qvXGTU0VRUDNZnEqF6s6dwfOPv/PtQZaoMTrK3jf9EXM3XNd2n8+I3E+CWHHly1j73vej6Drr\nPvhh1n7gQ4FTrwxp2ZC74TrGP/fZ4PlUwx+gHYfaY48BwvdDxsR/fBlralL0rfo1hFuvs+eNf0Dp\n3vYNq5+Q7wh8sBamy/ONQvh4TgxsxcITU159JuIRGI2e0WC1jWiK8GQvzDjwjrdy4K/fGvxf+iAF\nJfYRBqvDyFCcx2CFx7pj9jF+deR2/31iOI9qqJJ6EtUHO26sihAUNcJcSX+mWnh9OaUSiaRvXWAv\nz3wzZLB85rXu9+FTTXDskMGansIcHIqNrwCbHq9Td5Y2lgRZCUJ/JadUxM7Ngc9sNieENEQ2STSH\nhnA9D1VR0VUd23MwBgf914aXdayxfXHbpwiTeoL3Pusd/OXFf8IFA2G/2uwJMFiyMXg0RZjxqwjL\nVoWm0wzSaYvFuq41HCod9VvjSAYrDg0MnzVqNfdUFCVg1U3NINXZw8FhsW0praG2sbzQslmcSpn6\noYMkzwq1YrM//qH4Dl8nPfO979Ccmpr3fnlMp0LD59MWYEXDHB4hMbKShJ//lSErCcuPPBx7vqMS\nDmCVHdsAgpURiJtXPLe0FdYTHfICnH0SdWFL0WBNVsIeVNWKGEDTmfmeKWfixOOM0ejiIa9TXdGe\nUgbr4ent3DF2YgudXF2wWVK0GwVIvake5uq5WPqk9fhkmX8r66D4LJEEWPNtGpQAuMtUoRYBWG65\njG6ooHiwDIDleR5yd23LBzgNnylTTRRLNJT2bBtrdgZjcGCeTqi77CyZwaofPBg8dvwUoWfbQZPh\nxJq1wevmylVo3d1omQwernAw98GQuWULq//2PXS/aH5T5GNF07HYnz+4IIO1UIRmssfDYLmCwYqk\nCGUD6dmasCZK6scGWOs719B0moxVJuYVTMgIGKw2EgVpHaOrOoqicNeF4phKaXUeUAPQMhmRFpyc\nIHXW2egR8btdKARpXoDGkUOx93q2zcyXv8zWXbUzIveTLZIbz4r9363XsWamaY4ejT3fWY7oOeSK\nyC/rjb1/CWZpTq1G7sZfLLk1wFJCArzWVR+Aa1lL9hhZLBarIuxJiHTpZDUEWOWiuNjNxIm1mThV\novTAfYG+46mIaOWY/TT3aGsX8vwYvlbkqYqbj9zOdY//8pjbVa0aR0pjsee2zexkojLFTE2ksWQl\nV5TB6k/10XSaFCOVhI7rBOAJwgkuOil+6Dnv5iPPfa943m4HsEAhrr2CFgarUhEpHQNUa+H7umJV\nY9ocKXCHUIMVAiyZIlTF/eN5GAODgUO4jHTdpbZEgNU4GMoSokL2/M2/QuvoDKrYAAZf97usede7\n/XPgoSoiRQhguxapjWcdlw/WvRMP8KkHP0e+IcZmXVkawDI1A0M1jovBcn3PtKgGSzaQnqmL7MpS\nGKyze0QacXdu34IpQtkkuh2Dbrk2ht9bEeAVz/5dbr9qA7+4ojN2LcvQslnqjx/As23M4RHWfeij\nrP7b9wCQ/9WNOKXwN5RFaTJmrv4RpXvv5jkPleDA4WMe2687nlYAK+X3T5LhNuqU7r8PIKbV6irH\n02JqKhXcuFHwshQ32tJ99zD97f9i6lvfWPb+Fm67hcMf/uC85y1fV9AOYB352IfZ/1d/vuzvag15\no3m2TeH2W2MFATKVEQVYxbyg8+WK9XQOz/MY/+LnKdxy81P2nVG37TNmo/MjYLBU/SkFWIVmkXyj\ncMzig08++O989L5Px5772s5v88vDtzLrV5ZJxibKYMmqsJlaKEdwPXdeCkpV1MAfCKA70RUIlBVZ\nFecLhyUbFtNgyRRhXRyHYpoBG6SaHqo9HzAUbr+V8q4dvPO29/Pfu38Y7p+fHjRMDcd2cV0Pq+nv\ng6KiWH4fRH8cM/r6UVQVxQdZimGiudAoF+efyDbRnJoMHkcXPY2Dj5O9+JKY/5LRP4AxIETZruei\nogZs04k0Us83inh4FHyAZWhLd4PPGpnjFrlHNVhBA2k9zawP2pNLAFjdiS5WpAd5bG7vginCRRks\ntxmAVIDLh7fSe9GllNPaggBLpm4TK1eimibJ9RtIP+Nc5q79CYVbbwZVRe/tnQewKo8+Qursc6hn\nTPpv33HMY/t1x2kPsL6z+8f860NfAiC5IS74O/pPH2Xm+98ldfY5DP7uG9Df8BoAOitxgNXxzMtx\nKxU816URYbukM/BiIf0+irfd2rZMeLGoHzpE/cD+eeyX1H7J1g7Bd1nNYDV3IpUwEE5Ymx6cYPKr\n/0H5gfuD12RT0akYwBKTg2U9DRplOw44Dm7zqaOoo7qb1nLpMxEyrYb61DJYBX9ileX3C8VERYCA\nKPtYs2rkGnmKTcGOt2OwBlJ9gABYEhg5nhNLCwGs61wTsAytoTghwIqm7xQlBFZyv8yar6cZWhGM\nV6oJqjMfuM5e/SPyv7oJgLvG7wued/yUZNIXyFtNJwRYAA1QFSWo9NM6RLm/9GsyR0TFXbQQYLFw\nI/INeybOKnc883Kyl2yl+0UvIbv1UvSurvB9eEEVIZwYwJIidVnxuVQGC0Ql4fGkCG3flFZTNf7X\nWb/B31z2V4Bwh5/2AflSUoQAm3vPZl/+cep+ZZ7aAozk9Wa1YbCqVp2UHk/xykV4uwxI+hmhBs0c\nFr+1oqqs/Mu3ie+YnkLLZDCHR0LtnB9utYoxMMjcxRsYGC3SaHn9ZIvTHmDdOnonj+X2AqB3dVN8\n/sX84vJ4ZUPX/3g+iqriZMRF0gqwzOGV4Hm41SpWRHS3FAbLyuWCx9GV1lJClhXLgUiGXPm1Nqyu\nbNsWbhP53uMJOZj2TsoUaXisciCSK2/P8yIM1ukPsDzbd6V+AtO+x4poCsZqU+W0a3ZPoLt4OsSe\n3P4YwJfnx3gKGay6XQ80cVPVpaWLo+yjaXmojx0gUxX7HjTdVaIaLMFgfX3Xd/jGru8CAmBFGQOA\nc7o3YE1PB6XvsYj6OvkgC6D62M6gItGJMFieAsbAQCCP0BWX7qKGZYfXu+t6OPU6TpuWY5LBkgJ5\nq+lg2WHaEEsYWNplCbDEeCwZeXNYiMydYlhEs1g41WogXrempwMmDCC1aTNaOsPg636XkTe/JfC6\nAjHGRTVYtmsxWh6P6d2WGhIglfxU7lI1WCAA1nIYrKnqNHv8dJ7qs50vWvM8hjPCjyprZIICpKWk\nCAE29ZyF5VrsmTkAtNFgaQszWDW7Grbo8UMCrHaALLv1MhTTBEWJpYYVXUfL+tdCJoM5PExzYjyW\nPXGqFdRMBv3yS3EVmL7zliUd368rTnuA1RrTzz2XfWsS1JM6A695LcNvfgsdz7oCANv0fWTKDp5p\n0HPVK1jxxj9BywrRnlMuicoUBIXeToPVGBsNqHUAOx9Oeq2rq2OF7JfYqv+SKcLoyg2EwWq4zYlV\nOMqVR9bXVlkz4WQm0yG5RgHP82Ir1NhK9TQNz7L9v08dwLI9Jxj0rBYGy/M8vrjta9x05NanbH9+\n3fGZh77AP9z9T8H/A4Cg6k+ZyF2mgwCmawvf21HAV4949ySbHi+5cYzf+YUYI2r+JBtNEUZTgfdO\nPMje3AFs14lVjgGs7ljJ3PU/Zezzn6U1FNvB8Ud6z3HwfIapvnsXyaZf7ScZrLqNnTTQsh3BAjI9\nPU2ioVM7FGqdbvjRDnZ2XNK2p6vUYOmemFytpk0zKh2wFFRFDRksv7pbAqzEyEqxr6X546vnedRa\njCndahWjX7SGsWamMYdH0Lq6GHz97wXViu3C801VZd/Ao+VxPnzvpwJfsuWENIOVFaFRq41jRdbI\nUGrO1/guFNce+Dlf3v5NHM9tm4KTqWEgps9aLDZ2izY3O6Z2A2HjcBkyDfnVnf8dW9gAVKxa0HVA\nRtIHWO0AmaIobPjEp1n/8X+e95rmM4xaJou5Yhiv0QjmUM+28RoNtHSaoRXrme7Rqew6udOEpzXA\nitLxclVSdxo0DZUfvv5sel56JR1bLw1EjbYhLtauioubTjHwv3+H1GWXoWT81hPlMnYuh9bRid7V\nPS9F6LkuRz7yj8xec3W4D7lcIK63ZmeY+dEPOPzhD9A4cth/bpZDH3hfW8+PYzFYUSAH0Bw9GtDt\nJ2oh4XoumapDtiRukChzZ7kWuqJhuzZlqxIDVU+HFKFM2T7VDFbK7znWKnKv2TWarnVcOo7TJeQ5\nSWiJp8ymodAMAdZUdQbP8/jRvp8GnkIy5uphqqvRDH+jrM9cdVZcOowsVbuGbnvz9C8bu9ajKRqG\nqvPphz6PhxcwWIaq81tnvZILBs7FKZaElCHq2O444Lo0jbDhc0lWTXvQVYpXEZp1GytpomYyOJUK\nnuehY2GpJnYpZJTmpspUjK55LDqEbXLUohiDGrUmdozBUkQz4XIJNZMJWCVZSSjTRpTmp80qjzzM\nkY/8I/XDYXWZU61i9A8E/9c7O9n4yc/Q/cLFqwFdPN8HS4BYWc1Zai6/+XKQIvTf28owLhYj2WFm\n6nNL/t7J6jQVq0qxUWxbpSd7WMLSNFggWLSRzAqmq76+dwEGq2bXuW307thrVbtGagEGayFbGS2d\nxoho42RIv0ktnQ6ug+boKG6zGVTyq5kMI5kVHB0y4fAo9dqJF3U9WXFaA6yoT5NMa9V9d+B2QmHb\nCE+HmxYX5ltveTfXTQsXdwGw5tB7eoSXR7kU0zrZs7O4tRqNyM1v53KYwyOomQzFu+9i7qc/oX7g\nAJN+n8Oxz/0bjcOHmPned6hsD1N8EKYAZdUgCBAnwVOUwfI8j8boKJnzzhfHO3viAKvbH3wVw6Dp\ne814nofl2gymxYA2V8/FQNXJJHL3XPe46P5jfq4PrJZbGXrfxEOB3ma54XhOoKdo1Yq0anhOpThY\nPMzjhUPH3vAYIVN1KT35hDFYrufyvjs/ykNT29q+LivGMnqa6eoMdafOjYdv4eGp7bHtouxWox5O\nBh2VcD/7Ur2MHK3w59+dxjgaZwj+4qI38onnfYC3XfJm1nQIqxkJCnqS3bxkzfMFI1SZX4gjx4Fq\nUoxtnm0H7WkUvKCgRzKAZt3GSZlCiOw4eI06ug62ZlLxJQ63XPslysUytmrGAJa812SKUG+I/WnM\nFWJjhGdrAYMl04MQMljG4CCuqjCyc4Ly/gOxcxEsTOV4JPexP9LcuMXvcKHwvLgGSy5Qjqf8X5rB\nSsuM5aQIt/QKL6jduX3ccPAmHplemJXxPC9gkCaqU3QlOudtI41mNUWjJ9k97/WFQrJY0KaKMGJm\n+ujMzti4WrWqZOZpsMT/2zFYi4XeJfZXzWQwV4hU8ehn/pl9f/YngX2Dlk6TNTPkVnajOC7/cvX7\neLxwclYUntYAa64epuekaZ00J2u0+eGtCMBysqngInqgKjRc1d2PYeVy6D09qJkM1Z07OPj37w62\na4yLMuzG4UNM/+B71PbvwykW0Ht6MPr6BcPU1UXmootxikUBig4fovulV4KiUNu3J7Y/7RgsO5/D\ns220DtEKSOannUIet1ohsX49WkfnE8JgScPV5MazsKanRK9Gz8HDY8gHWLl6PmCwVE05aRgst9Fg\n/1v/gvJDDz7hn308Gqy6XeerO/+bTz/4heP6TsdzAj1Fa4pQ9hFbqm/QyRQ/3vczfrTvZ8t6T1SP\nJlNuzQjAeqI0WOOVSWbqc/xw37VtX5cpwrO61zNdmw0AVyuTOF0N78VmLXytoxoeR1+yh5VT4nfV\n98UBp6EZmJrBms5VPHvkmYBIZ0GcoQj68EX0kqV77gJg/xox4XmOjZWXC08vWERJ0J5oONgpM0jb\nOZUKaVPHUzRmRg+Rn6tSuucgrmdgayZeBGDJsVWmCNWK31NwNkejEgEtjiYqGMvlQHMDIcDSMllU\n16MrV2fnBz8cOxcSHEqNqVxkGn0hwIqyWYuF67moihKkCKt+w+XlVul6nhcwWKXm8lOEqztWktZT\n/OLQzVxz4Hq+uO1rC25baBZjRS5rO1bN20aySes618wrhlgs1neuCR63MmNRsfxMbZaJarjgrthV\n0kY8RRgwWMs8lwGDlcmidXaipkOwbOcFwyifS5x1FrYKa49U6DCXBqqf6jitAVZU9CuZq2BAdpvz\n2A1bA9dP2dudmWCgLqc1Op/7PPK/uIHm0SPoPb3BABR1dG/6AMut18ld91OO/tNHwfMCxgug49Jn\nonf30KyW2DuxC1wXvbsbvbcXazqu4wg0WBGA1ZwQJqPJjRuF8N4HYbJnYmJkJXpf3xPCYKXr4vhT\nGzbiNRo4xbAcXTJY1x38JUfy4riz2QT2MjVYY4fzwYr3iQynWMStVuY1k30iwjuOFKEcFCer852J\nlxKO6wS6hlaAdSozWA2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zu0CvscTadQBUHnkIINZYtDVklZE0/essi89X0xmS69fTfPZF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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1084ae6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_random_series(df, n_series):\n",
    "    \n",
    "    sample = df.sample(n_series, random_state=8)\n",
    "    page_labels = sample['Page'].tolist()\n",
    "    series_samples = sample.loc[:,data_start_date:data_end_date]\n",
    "    \n",
    "    plt.figure(figsize=(10,6))\n",
    "    \n",
    "    for i in range(series_samples.shape[0]):\n",
    "        np.log1p(pd.Series(series_samples.iloc[i]).astype(np.float64)).plot(linewidth=1.5)\n",
    "    \n",
    "    plt.title('Randomly Selected Wikipedia Page Daily Views Over Time (Log(views) + 1)')\n",
    "    plt.legend(page_labels)\n",
    "    \n",
    "plot_random_series(df, 6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Formatting the Data for Modeling \n",
    "\n",
    "Sadly we can't just throw the dataframe we've created into keras and let it work its magic. Instead, we have to set up a few data transformation steps to extract nice numpy arrays that we can pass to keras. But even before doing that, we have to know how to appropriately partition the time series into encoding and prediction intervals for the purposes of training and validation. Note that for our simple convolutional model we won't use an encoder-decoder architecture like in the first notebook, but **we'll keep the \"encoding\" and \"decoding\" (prediction) terminology to be consistent** -- in this case, the encoding interval represents the entire series history that we will use for the network's feature learning, but not output any predictions on. \n",
    "\n",
    "We'll use a style of **walk-forward validation**, where our validation set spans the same time-range as our training set, but shifted forward in time (in this case by 60 days). This way, we simulate how our model will perform on unseen data that comes in the future. \n",
    "\n",
    "[Artur Suilin](https://github.com/Arturus/kaggle-web-traffic/blob/master/how_it_works.md) has created a very nice image that visualizes this validation style and contrasts it with traditional validation. I highly recommend checking out his entire repo, as he's implemented a truly state of the art (and competition winning) seq2seq model on this data set. \n",
    "\n",
    "![architecture](images/ArturSuilin_validation.png)\n",
    "\n",
    "### Train and Validation Series Partioning\n",
    "\n",
    "We need to create 4 sub-segments of the data:\n",
    "\n",
    "    1. Train encoding period\n",
    "    2. Train decoding period (train targets, 60 days)\n",
    "    3. Validation encoding period\n",
    "    4. Validation decoding period (validation targets, 60 days)\n",
    "    \n",
    "We'll do this by finding the appropriate start and end dates for each segment. Starting from the end of the data we've loaded, we'll work backwards to get validation and training prediction intervals. Then we'll work forward from the start to get training and validation encoding intervals. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from datetime import timedelta\n",
    "\n",
    "pred_steps = 60 \n",
    "pred_length=timedelta(pred_steps)\n",
    "\n",
    "first_day = pd.to_datetime(data_start_date) \n",
    "last_day = pd.to_datetime(data_end_date)\n",
    "\n",
    "val_pred_start = last_day - pred_length + timedelta(1)\n",
    "val_pred_end = last_day\n",
    "\n",
    "train_pred_start = val_pred_start - pred_length\n",
    "train_pred_end = val_pred_start - timedelta(days=1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "enc_length = train_pred_start - first_day\n",
    "\n",
    "train_enc_start = first_day\n",
    "train_enc_end = train_enc_start + enc_length - timedelta(1)\n",
    "\n",
    "val_enc_start = train_enc_start + pred_length\n",
    "val_enc_end = val_enc_start + enc_length - timedelta(1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train encoding: 2015-07-01 00:00:00 - 2016-09-02 00:00:00\n",
      "Train prediction: 2016-09-03 00:00:00 - 2016-11-01 00:00:00 \n",
      "\n",
      "Val encoding: 2015-08-30 00:00:00 - 2016-11-01 00:00:00\n",
      "Val prediction: 2016-11-02 00:00:00 - 2016-12-31 00:00:00\n",
      "\n",
      "Encoding interval: 430\n",
      "Prediction interval: 60\n"
     ]
    }
   ],
   "source": [
    "print('Train encoding:', train_enc_start, '-', train_enc_end)\n",
    "print('Train prediction:', train_pred_start, '-', train_pred_end, '\\n')\n",
    "print('Val encoding:', val_enc_start, '-', val_enc_end)\n",
    "print('Val prediction:', val_pred_start, '-', val_pred_end)\n",
    "\n",
    "print('\\nEncoding interval:', enc_length.days)\n",
    "print('Prediction interval:', pred_length.days)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Keras Data Formatting\n",
    "\n",
    "Now that we have the time segment dates, we'll define the functions we need to extract the data in keras friendly format. Here are the steps:\n",
    "\n",
    "* Pull the time series into an array, save a date_to_index mapping as a utility for referencing into the array \n",
    "* Create function to extract specified time interval from all the series \n",
    "* Create functions to transform all the series. \n",
    "    - Here we smooth out the scale by taking log1p and de-meaning each series using the encoder series mean, then reshape to the **(n_series, n_timesteps, n_features) tensor format** that keras will expect. \n",
    "    - Note that if we want to generate true predictions instead of log scale ones, we can easily apply a reverse transformation at prediction time. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "date_to_index = pd.Series(index=pd.Index([pd.to_datetime(c) for c in df.columns[1:]]),\n",
    "                          data=[i for i in range(len(df.columns[1:]))])\n",
    "\n",
    "series_array = df[df.columns[1:]].values\n",
    "\n",
    "def get_time_block_series(series_array, date_to_index, start_date, end_date):\n",
    "    \n",
    "    inds = date_to_index[start_date:end_date]\n",
    "    return series_array[:,inds]\n",
    "\n",
    "def transform_series_encode(series_array):\n",
    "    \n",
    "    series_array = np.log1p(np.nan_to_num(series_array)) # filling NaN with 0\n",
    "    series_mean = series_array.mean(axis=1).reshape(-1,1) \n",
    "    series_array = series_array - series_mean\n",
    "    series_array = series_array.reshape((series_array.shape[0],series_array.shape[1], 1))\n",
    "    \n",
    "    return series_array, series_mean\n",
    "\n",
    "def transform_series_decode(series_array, encode_series_mean):\n",
    "    \n",
    "    series_array = np.log1p(np.nan_to_num(series_array)) # filling NaN with 0\n",
    "    series_array = series_array - encode_series_mean\n",
    "    series_array = series_array.reshape((series_array.shape[0],series_array.shape[1], 1))\n",
    "    \n",
    "    return series_array"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Building the Model - Architecture\n",
    "\n",
    "This convolutional architecture is a full-fledged version of the [WaveNet model](https://deepmind.com/blog/wavenet-generative-model-raw-audio/), designed as a generative model for audio (in particular, for text-to-speech applications). The wavenet model can be abstracted beyond audio to apply to any time series forecasting problem, providing a nice structure for capturing long-term dependencies without an excessive number of learned weights.\n",
    "\n",
    "The core building block of the wavenet model is the **dilated causal convolution layer**, discussed in detail in the [previous notebook of this series](https://github.com/JEddy92/TimeSeries_Seq2Seq/blob/master/notebooks/TS_Seq2Seq_Conv_Intro.ipynb) as well as the [accompanying blog post](https://jeddy92.github.io/JEddy92.github.io/ts_seq2seq_conv/). In summary, this style of convolution properly handles temporal flow and allows the receptive field of outputs to increase exponentially as a function of the number of layers. This structure is nicely visualized by the below diagram from the wavenet paper. \n",
    "\n",
    "![dilatedconv](images/WaveNet_dilatedconv.png)\n",
    "\n",
    "The model also utilizes some other key techniques: **gated activations**, **residual connections**, and **skip connections**. I'll introduce and explain these techniques, then show how to implement our full-fledged WaveNet architecture in keras. The WaveNet paper diagram below details how the model's components fit together block by block into a stack of operations, so we'll use it as a handy reference as we go (note that there are slight discrepancies between the diagram and what we implement, e.g. the original WaveNet has a softmax classification rather than regression output).   \n",
    "\n",
    "![blocks](images/WaveNet_residblock.png)\n",
    "\n",
    "### **Gated Activations**\n",
    "\n",
    "In the boxed portion of the architecture diagram, you'll notice that the dilated convolution output splits into two branches that are later recombined via element-wise multiplication. This depicts a *gated activation unit*, where we interpret the *tanh* activation branch as a learned filter and the *sigmoid* activation branch as a learned gate that regulates the information flow from the filter. If this reminds you of the gating mechanisms used in [LSTMs or GRUs](http://colah.github.io/posts/2015-08-Understanding-LSTMs/) you're on point, as those models use the same style of information gating to control adjustments to their cell states.\n",
    "\n",
    "In mathematical notation, this means we map a convolutional block's input $x$ to output $z$ via the below, where $W_f$ and $W_g$ correspond to (learned) dilated causal convolution weights:\n",
    "\n",
    "$$ z = tanh(W_f * x) \\odot \\sigma(W_g * x) $$\n",
    "\n",
    "Why use gated activations instead of the more standard *ReLU* activation? The WaveNet designers found that gated activations saw stronger performance empirically than ReLU activations for audio data, and this outperformance may extend broadly to time series data. Perhaps the [sparsity induced by ReLU activations](http://proceedings.mlr.press/v15/glorot11a.html) is not as well suited to time series forecasting as it is to other problem domains, or gated activations allow for smoother information (gradient) flow over a many-layered WaveNet architecture. However, this choice of activation is certainly not set in stone and I'd be interested to see a results comparison when trying ReLU instead. With that caveat, we'll be sticking with the gated activations in the interest of learning about the full original architecture.            \n",
    "\n",
    "### **Residual and Skip Connections**\n",
    "\n",
    "In traditional neural network architectures, a neuron layer takes direct input only from the layer that precedes it, so early layers influence deeper layers via a heirarchy of intermediate computations. In theory, this heirarchy allows the network to properly build up high-level predictive features off of lower-level/raw signals. For example, in image classification problems, neural nets start from raw pixel values, find generic geometric and textural patterns, then combine these generic patterns to construct fine-grained representations of the features that identify specific object types.\n",
    "\n",
    "But what if lower-level signals are actually immediately useful for prediction, and may be at risk of distortion as they're passed through a complex heirarchy of computations? We could always simplify the heirarchy by using fewer layers and units, but what if we want the best of both worlds: direct, unfiltered low-level signals and nuanced heirarchical representations? One avenue for addressing this problem is provided by **skip connections**, which act to preserve earlier feature layer outputs as the network passes forward signals for final prediction processing. To build intuition for why we would want a mix of feature complexities in our problem domain, consider the wide range of time series drivers - there are strong and direct autoregressive components, moderately more sophisticated trend and seasonality components, and idiosyncratic trajectories that are difficult to spot with the human eye.        \n",
    "\n",
    "To leverage skip connections, we can simply store the tensor output of each convolutional block in addition to passing it through further blocks (or choose select blocks to store output from). At the end of the block heirarchy, we then have a collection of feature outputs at *all levels of the heirarchy*, rather than a singular set of maximally complex feature outputs. This collection of outputs is then combined for final processing, typically via concatenation or addition (we'll use the latter).\n",
    "\n",
    "With this in mind, return to the WaveNet block diagram above, and notice how for each block in the stack, the post-convolution gated activations pass through to the set of skip connections. This visualizes the tensor output storage and eventual combination just described. Note that the frequency and structure of skip connections is fully customizable and can be chosen experimentally and via domain expertise - as an example of an alternate skip connection structure, check out this convolutional architecture from a [semantic segmentation paper](https://www.researchgate.net/publication/327330378_Semantic_Segmentation_Based_on_Deep_Convolution_Neural_Network).\n",
    "\n",
    "![CNN_skips](images/CNN_skips.png)\n",
    "\n",
    "**Residual connections** are closely related to skip connections; in fact, they can be viewed as specialized, short skips further into the network (often and in our case just one layer). With residual connections, we think of mapping a network block's input to output via $x_{out} = f(x_{in}) + x_{in}$ instead of using the traditional direct mapping $x_{out} = f(x_{in})$, for some function $f$ that corresponds to the model's learned weights. This helps allow for the possibility that the model learns a mapping that acts almost as an identity function, with the input passing through nearly unchanged. In the diagram above, such connections are visualized by the rounded arrows grouped with each pair of convolutions.  \n",
    "\n",
    "Why would this be beneficial? Well, the effectiveness of residual connections is still not fully understood, but a compelling explanation is that they facilitate the use of deeper networks by allowing for more direct gradient flow in backpropagation. It's often difficult to efficienctly train the early layers of a deep network due to the length of the backpropagation chain, but residual and skip connections create an easier information highway. Intuitively, perhaps you can think of both as mechanisms for guarding against overcomputation and intermediate signal loss. You can check out the [ResNet paper](https://arxiv.org/pdf/1512.03385.pdf) that originated the residual connection concept for more discussion and empirical results.\n",
    "\n",
    "Though our architecture will be shallower than the original WaveNet (fewer convolutional blocks), we'll likely still see some benefit from introducing skip and residual connections at every block. Returning to the WaveNet architecture diagram again, you can see how the residual connection allows each block's input to bypass the convolution stage, and then adds that input to the convolution output. A final point to note is that the diagram's *1x1 convolutions* are really just equivalent to (time-distributed) fully connected layers, and serve in post-processing and standardization capacities. Our setup will use layers of this style (with different filter dimensions) for **post/pre-processing** to facilitate our skip and residual connections, as well as for generating final prediction outputs.           \n",
    "\n",
    "### **Our Architecture**\n",
    "\n",
    "With all of our components now laid out, here's what we'll use:\n",
    "\n",
    "* 16 dilated causal convolutional blocks\n",
    "    * Preprocessing and postprocessing (time distributed) fully connected layers (convolutions with filter width 1): 16 output units\n",
    "    * 32 filters of width 2 per block\n",
    "    * Exponentially increasing dilation rate with a reset (1, 2, 4, 8, ..., 128, 1, 2, ..., 128) \n",
    "    * Gated activations\n",
    "    * Residual and skip connections\n",
    "* 2 (time distributed) fully connected layers to map sum of skip outputs to final output \n",
    "\n",
    "We'll extract the last 60 steps from the output sequence as our predicted output for training. We'll use teacher forcing again during training. Similarly to the previous notebook, we'll have a separate function that runs an inference loop to generate predictions on unseen data, iteratively filling previous predictions into the history sequence (section 4). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Model\n",
    "from keras.layers import Input, Conv1D, Dense, Activation, Dropout, Lambda, Multiply, Add, Concatenate\n",
    "from keras.optimizers import Adam\n",
    "\n",
    "# convolutional operation parameters\n",
    "n_filters = 32 # 32 \n",
    "filter_width = 2\n",
    "dilation_rates = [2**i for i in range(8)] * 2 \n",
    "\n",
    "# define an input history series and pass it through a stack of dilated causal convolution blocks. \n",
    "history_seq = Input(shape=(None, 1))\n",
    "x = history_seq\n",
    "\n",
    "skips = []\n",
    "for dilation_rate in dilation_rates:\n",
    "    \n",
    "    # preprocessing - equivalent to time-distributed dense\n",
    "    x = Conv1D(16, 1, padding='same', activation='relu')(x) \n",
    "    \n",
    "    # filter convolution\n",
    "    x_f = Conv1D(filters=n_filters,\n",
    "                 kernel_size=filter_width, \n",
    "                 padding='causal',\n",
    "                 dilation_rate=dilation_rate)(x)\n",
    "    \n",
    "    # gating convolution\n",
    "    x_g = Conv1D(filters=n_filters,\n",
    "                 kernel_size=filter_width, \n",
    "                 padding='causal',\n",
    "                 dilation_rate=dilation_rate)(x)\n",
    "    \n",
    "    # multiply filter and gating branches\n",
    "    z = Multiply()([Activation('tanh')(x_f),\n",
    "                    Activation('sigmoid')(x_g)])\n",
    "    \n",
    "    # postprocessing - equivalent to time-distributed dense\n",
    "    z = Conv1D(16, 1, padding='same', activation='relu')(z)\n",
    "    \n",
    "    # residual connection\n",
    "    x = Add()([x, z])    \n",
    "    \n",
    "    # collect skip connections\n",
    "    skips.append(z)\n",
    "\n",
    "# add all skip connection outputs \n",
    "out = Activation('relu')(Add()(skips))\n",
    "\n",
    "# final time-distributed dense layers \n",
    "out = Conv1D(128, 1, padding='same')(out)\n",
    "out = Activation('relu')(out)\n",
    "out = Dropout(.2)(out)\n",
    "out = Conv1D(1, 1, padding='same')(out)\n",
    "\n",
    "# extract the last 60 time steps as the training target\n",
    "def slice(x, seq_length):\n",
    "    return x[:,-seq_length:,:]\n",
    "\n",
    "pred_seq_train = Lambda(slice, arguments={'seq_length':60})(out)\n",
    "\n",
    "model = Model(history_seq, pred_seq_train)\n",
    "model.compile(Adam(), loss='mean_absolute_error')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, None, 1)      0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_1 (Conv1D)               (None, None, 16)     32          input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_2 (Conv1D)               (None, None, 32)     1056        conv1d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_3 (Conv1D)               (None, None, 32)     1056        conv1d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, None, 32)     0           conv1d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, None, 32)     0           conv1d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_1 (Multiply)           (None, None, 32)     0           activation_1[0][0]               \n",
      "                                                                 activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_4 (Conv1D)               (None, None, 16)     528         multiply_1[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, None, 16)     0           conv1d_1[0][0]                   \n",
      "                                                                 conv1d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_5 (Conv1D)               (None, None, 16)     272         add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_6 (Conv1D)               (None, None, 32)     1056        conv1d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_7 (Conv1D)               (None, None, 32)     1056        conv1d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, None, 32)     0           conv1d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, None, 32)     0           conv1d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "multiply_2 (Multiply)           (None, None, 32)     0           activation_3[0][0]               \n",
      "                                                                 activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_8 (Conv1D)               (None, None, 16)     528         multiply_2[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_2 (Add)                     (None, None, 16)     0           conv1d_5[0][0]                   \n",
      "                                                                 conv1d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_9 (Conv1D)               (None, None, 16)     272         add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_10 (Conv1D)              (None, None, 32)     1056        conv1d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_11 (Conv1D)              (None, None, 32)     1056        conv1d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, None, 32)     0           conv1d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, None, 32)     0           conv1d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_3 (Multiply)           (None, None, 32)     0           activation_5[0][0]               \n",
      "                                                                 activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_12 (Conv1D)              (None, None, 16)     528         multiply_3[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_3 (Add)                     (None, None, 16)     0           conv1d_9[0][0]                   \n",
      "                                                                 conv1d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_13 (Conv1D)              (None, None, 16)     272         add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_14 (Conv1D)              (None, None, 32)     1056        conv1d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_15 (Conv1D)              (None, None, 32)     1056        conv1d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, None, 32)     0           conv1d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, None, 32)     0           conv1d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_4 (Multiply)           (None, None, 32)     0           activation_7[0][0]               \n",
      "                                                                 activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_16 (Conv1D)              (None, None, 16)     528         multiply_4[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_4 (Add)                     (None, None, 16)     0           conv1d_13[0][0]                  \n",
      "                                                                 conv1d_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_17 (Conv1D)              (None, None, 16)     272         add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_18 (Conv1D)              (None, None, 32)     1056        conv1d_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_19 (Conv1D)              (None, None, 32)     1056        conv1d_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, None, 32)     0           conv1d_18[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, None, 32)     0           conv1d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_5 (Multiply)           (None, None, 32)     0           activation_9[0][0]               \n",
      "                                                                 activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_20 (Conv1D)              (None, None, 16)     528         multiply_5[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_5 (Add)                     (None, None, 16)     0           conv1d_17[0][0]                  \n",
      "                                                                 conv1d_20[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_21 (Conv1D)              (None, None, 16)     272         add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_22 (Conv1D)              (None, None, 32)     1056        conv1d_21[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_23 (Conv1D)              (None, None, 32)     1056        conv1d_21[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, None, 32)     0           conv1d_22[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, None, 32)     0           conv1d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_6 (Multiply)           (None, None, 32)     0           activation_11[0][0]              \n",
      "                                                                 activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_24 (Conv1D)              (None, None, 16)     528         multiply_6[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_6 (Add)                     (None, None, 16)     0           conv1d_21[0][0]                  \n",
      "                                                                 conv1d_24[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_25 (Conv1D)              (None, None, 16)     272         add_6[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_26 (Conv1D)              (None, None, 32)     1056        conv1d_25[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_27 (Conv1D)              (None, None, 32)     1056        conv1d_25[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, None, 32)     0           conv1d_26[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, None, 32)     0           conv1d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_7 (Multiply)           (None, None, 32)     0           activation_13[0][0]              \n",
      "                                                                 activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_28 (Conv1D)              (None, None, 16)     528         multiply_7[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_7 (Add)                     (None, None, 16)     0           conv1d_25[0][0]                  \n",
      "                                                                 conv1d_28[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_29 (Conv1D)              (None, None, 16)     272         add_7[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_30 (Conv1D)              (None, None, 32)     1056        conv1d_29[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_31 (Conv1D)              (None, None, 32)     1056        conv1d_29[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, None, 32)     0           conv1d_30[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, None, 32)     0           conv1d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_8 (Multiply)           (None, None, 32)     0           activation_15[0][0]              \n",
      "                                                                 activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_32 (Conv1D)              (None, None, 16)     528         multiply_8[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_8 (Add)                     (None, None, 16)     0           conv1d_29[0][0]                  \n",
      "                                                                 conv1d_32[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_33 (Conv1D)              (None, None, 16)     272         add_8[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_34 (Conv1D)              (None, None, 32)     1056        conv1d_33[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_35 (Conv1D)              (None, None, 32)     1056        conv1d_33[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, None, 32)     0           conv1d_34[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, None, 32)     0           conv1d_35[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_9 (Multiply)           (None, None, 32)     0           activation_17[0][0]              \n",
      "                                                                 activation_18[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_36 (Conv1D)              (None, None, 16)     528         multiply_9[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "add_9 (Add)                     (None, None, 16)     0           conv1d_33[0][0]                  \n",
      "                                                                 conv1d_36[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_37 (Conv1D)              (None, None, 16)     272         add_9[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_38 (Conv1D)              (None, None, 32)     1056        conv1d_37[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_39 (Conv1D)              (None, None, 32)     1056        conv1d_37[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, None, 32)     0           conv1d_38[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, None, 32)     0           conv1d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_10 (Multiply)          (None, None, 32)     0           activation_19[0][0]              \n",
      "                                                                 activation_20[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_40 (Conv1D)              (None, None, 16)     528         multiply_10[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "add_10 (Add)                    (None, None, 16)     0           conv1d_37[0][0]                  \n",
      "                                                                 conv1d_40[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_41 (Conv1D)              (None, None, 16)     272         add_10[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_42 (Conv1D)              (None, None, 32)     1056        conv1d_41[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_43 (Conv1D)              (None, None, 32)     1056        conv1d_41[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, None, 32)     0           conv1d_42[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, None, 32)     0           conv1d_43[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_11 (Multiply)          (None, None, 32)     0           activation_21[0][0]              \n",
      "                                                                 activation_22[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_44 (Conv1D)              (None, None, 16)     528         multiply_11[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "add_11 (Add)                    (None, None, 16)     0           conv1d_41[0][0]                  \n",
      "                                                                 conv1d_44[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_45 (Conv1D)              (None, None, 16)     272         add_11[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_46 (Conv1D)              (None, None, 32)     1056        conv1d_45[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_47 (Conv1D)              (None, None, 32)     1056        conv1d_45[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, None, 32)     0           conv1d_46[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, None, 32)     0           conv1d_47[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_12 (Multiply)          (None, None, 32)     0           activation_23[0][0]              \n",
      "                                                                 activation_24[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_48 (Conv1D)              (None, None, 16)     528         multiply_12[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "add_12 (Add)                    (None, None, 16)     0           conv1d_45[0][0]                  \n",
      "                                                                 conv1d_48[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_49 (Conv1D)              (None, None, 16)     272         add_12[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_50 (Conv1D)              (None, None, 32)     1056        conv1d_49[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_51 (Conv1D)              (None, None, 32)     1056        conv1d_49[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, None, 32)     0           conv1d_50[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_26 (Activation)      (None, None, 32)     0           conv1d_51[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_13 (Multiply)          (None, None, 32)     0           activation_25[0][0]              \n",
      "                                                                 activation_26[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_52 (Conv1D)              (None, None, 16)     528         multiply_13[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "add_13 (Add)                    (None, None, 16)     0           conv1d_49[0][0]                  \n",
      "                                                                 conv1d_52[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_53 (Conv1D)              (None, None, 16)     272         add_13[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_54 (Conv1D)              (None, None, 32)     1056        conv1d_53[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_55 (Conv1D)              (None, None, 32)     1056        conv1d_53[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_27 (Activation)      (None, None, 32)     0           conv1d_54[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_28 (Activation)      (None, None, 32)     0           conv1d_55[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_14 (Multiply)          (None, None, 32)     0           activation_27[0][0]              \n",
      "                                                                 activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_56 (Conv1D)              (None, None, 16)     528         multiply_14[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "add_14 (Add)                    (None, None, 16)     0           conv1d_53[0][0]                  \n",
      "                                                                 conv1d_56[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_57 (Conv1D)              (None, None, 16)     272         add_14[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_58 (Conv1D)              (None, None, 32)     1056        conv1d_57[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_59 (Conv1D)              (None, None, 32)     1056        conv1d_57[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_29 (Activation)      (None, None, 32)     0           conv1d_58[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_30 (Activation)      (None, None, 32)     0           conv1d_59[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_15 (Multiply)          (None, None, 32)     0           activation_29[0][0]              \n",
      "                                                                 activation_30[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_60 (Conv1D)              (None, None, 16)     528         multiply_15[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "add_15 (Add)                    (None, None, 16)     0           conv1d_57[0][0]                  \n",
      "                                                                 conv1d_60[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_61 (Conv1D)              (None, None, 16)     272         add_15[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_62 (Conv1D)              (None, None, 32)     1056        conv1d_61[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_63 (Conv1D)              (None, None, 32)     1056        conv1d_61[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_31 (Activation)      (None, None, 32)     0           conv1d_62[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_32 (Activation)      (None, None, 32)     0           conv1d_63[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "multiply_16 (Multiply)          (None, None, 32)     0           activation_31[0][0]              \n",
      "                                                                 activation_32[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_64 (Conv1D)              (None, None, 16)     528         multiply_16[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "add_17 (Add)                    (None, None, 16)     0           conv1d_4[0][0]                   \n",
      "                                                                 conv1d_8[0][0]                   \n",
      "                                                                 conv1d_12[0][0]                  \n",
      "                                                                 conv1d_16[0][0]                  \n",
      "                                                                 conv1d_20[0][0]                  \n",
      "                                                                 conv1d_24[0][0]                  \n",
      "                                                                 conv1d_28[0][0]                  \n",
      "                                                                 conv1d_32[0][0]                  \n",
      "                                                                 conv1d_36[0][0]                  \n",
      "                                                                 conv1d_40[0][0]                  \n",
      "                                                                 conv1d_44[0][0]                  \n",
      "                                                                 conv1d_48[0][0]                  \n",
      "                                                                 conv1d_52[0][0]                  \n",
      "                                                                 conv1d_56[0][0]                  \n",
      "                                                                 conv1d_60[0][0]                  \n",
      "                                                                 conv1d_64[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_33 (Activation)      (None, None, 16)     0           add_17[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_65 (Conv1D)              (None, None, 128)    2176        activation_33[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_34 (Activation)      (None, None, 128)    0           conv1d_65[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, None, 128)    0           activation_34[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_66 (Conv1D)              (None, None, 1)      129         dropout_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lambda_1 (Lambda)               (None, None, 1)      0           conv1d_66[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 48,657\n",
      "Trainable params: 48,657\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With our training architecture defined, we're ready to train the model! This will take quite a while if you're not running fancy hardware (read GPU). We'll leverage the transformer utility functions we defined earlier, and train using mean absolute error loss.\n",
    "\n",
    "Note that for this full-fledged model, we have more than twice as many total parameters to train as we did with the simpler WaveNet model, explaining the slower training time (along with using more training data). From the loss curve you'll see plotted below, it also seems likely that the model can continue to improve with more than 10 training epochs -- the more complex model probably needs additional time to reach its full potential. That said, from the results plots (see section 5) we can see that this full-fledged model is very capable of handling the 60-day forecast horizon and often can generate very expressive predictions. \n",
    "\n",
    "This is only a starting point, and I would encourage you to play around with this architecture to see if you can get even better results! You could try using more data, adjusting the hyperparameters, tuning the learning rate and number of epochs, etc.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 96000 samples, validate on 24000 samples\n",
      "Epoch 1/10\n",
      "96000/96000 [==============================] - 1443s 15ms/step - loss: 0.4242 - val_loss: 0.2930\n",
      "Epoch 2/10\n",
      "96000/96000 [==============================] - 1408s 15ms/step - loss: 0.3065 - val_loss: 0.2724\n",
      "Epoch 3/10\n",
      "96000/96000 [==============================] - 1392s 14ms/step - loss: 0.2884 - val_loss: 0.2588\n",
      "Epoch 4/10\n",
      "96000/96000 [==============================] - 1399s 15ms/step - loss: 0.2800 - val_loss: 0.2535\n",
      "Epoch 5/10\n",
      "96000/96000 [==============================] - 1379s 14ms/step - loss: 0.2750 - val_loss: 0.2505\n",
      "Epoch 6/10\n",
      "96000/96000 [==============================] - 1401s 15ms/step - loss: 0.2719 - val_loss: 0.2483\n",
      "Epoch 7/10\n",
      "96000/96000 [==============================] - 1431s 15ms/step - loss: 0.2699 - val_loss: 0.2466\n",
      "Epoch 8/10\n",
      "96000/96000 [==============================] - 1428s 15ms/step - loss: 0.2684 - val_loss: 0.2457\n",
      "Epoch 9/10\n",
      "96000/96000 [==============================] - 1431s 15ms/step - loss: 0.2673 - val_loss: 0.2440\n",
      "Epoch 10/10\n",
      "96000/96000 [==============================] - 1434s 15ms/step - loss: 0.2662 - val_loss: 0.2431\n"
     ]
    }
   ],
   "source": [
    "first_n_samples = 120000\n",
    "batch_size = 2**11\n",
    "epochs = 10\n",
    "\n",
    "# sample of series from train_enc_start to train_enc_end  \n",
    "encoder_input_data = get_time_block_series(series_array, date_to_index, \n",
    "                                           train_enc_start, train_enc_end)[:first_n_samples]\n",
    "encoder_input_data, encode_series_mean = transform_series_encode(encoder_input_data)\n",
    "\n",
    "# sample of series from train_pred_start to train_pred_end \n",
    "decoder_target_data = get_time_block_series(series_array, date_to_index, \n",
    "                                            train_pred_start, train_pred_end)[:first_n_samples]\n",
    "decoder_target_data = transform_series_decode(decoder_target_data, encode_series_mean)\n",
    "\n",
    "# we append a lagged history of the target series to the input data, \n",
    "# so that we can train with teacher forcing\n",
    "lagged_target_history = decoder_target_data[:,:-1,:1]\n",
    "encoder_input_data = np.concatenate([encoder_input_data, lagged_target_history], axis=1)\n",
    "\n",
    "model.compile(Adam(), loss='mean_absolute_error')\n",
    "history = model.fit(encoder_input_data, decoder_target_data,\n",
    "                    batch_size=batch_size,\n",
    "                    epochs=epochs,\n",
    "                    validation_split=0.2)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's typically a good idea to look at the convergence curve of train/validation loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1a2fc58d30>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Tw4cPezL8SwoP8SMyxE/mDRNCeMzgwYl8/vlahgwZBkC7dlfRrt3VjBqVxP3330NISChn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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2ae463c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'])\n",
    "plt.plot(history.history['val_loss'])\n",
    "\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Mean Absolute Error Loss')\n",
    "plt.title('Loss Over Time')\n",
    "plt.legend(['Train','Valid'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Building the Model - Inference Loop\n",
    "\n",
    "Like in the previous notebook, we'll generate predictions by running our model from section 3 in a loop, using each iteration to extract the prediction for the time step one beyond our current history then append it to our history sequence. With 60 iterations, this lets us generate predictions for the full interval we've chosen. \n",
    "\n",
    "Recall that we designed our model to output predictions for 60 time steps at once in order to use teacher forcing for training. So if we start from a history sequence and want to predict the first future time step, we can run the model on the history sequence and take the last time step of the output, which corresponds to one time step beyond the history sequence. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def predict_sequence(input_sequence):\n",
    "\n",
    "    history_sequence = input_sequence.copy()\n",
    "    pred_sequence = np.zeros((1,pred_steps,1)) # initialize output (pred_steps time steps)  \n",
    "    \n",
    "    for i in range(pred_steps):\n",
    "        \n",
    "        # record next time step prediction (last time step of model output) \n",
    "        last_step_pred = model.predict(history_sequence)[0,-1,0]\n",
    "        pred_sequence[0,i,0] = last_step_pred\n",
    "        \n",
    "        # add the next time step prediction to the history sequence\n",
    "        history_sequence = np.concatenate([history_sequence, \n",
    "                                           last_step_pred.reshape(-1,1,1)], axis=1)\n",
    "\n",
    "    return pred_sequence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Generating and Plotting Predictions \n",
    "\n",
    "Now we have everything we need to generate predictions for encoder (history) /target series pairs that we didn't train on (note again we're using \"encoder\"/\"decoder\" terminology to stay consistent with notebook 1 -- here it's more like history/target). We'll pull out our set of validation encoder/target series (recall that these are shifted forward in time). Then using a plotting utility function, we can look at the tail end of the encoder series, the true target series, and the predicted target series. This gives us a feel for how our predictions are doing.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "encoder_input_data = get_time_block_series(series_array, date_to_index, val_enc_start, val_enc_end)\n",
    "encoder_input_data, encode_series_mean = transform_series_encode(encoder_input_data)\n",
    "\n",
    "decoder_target_data = get_time_block_series(series_array, date_to_index, val_pred_start, val_pred_end)\n",
    "decoder_target_data = transform_series_decode(decoder_target_data, encode_series_mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def predict_and_plot(encoder_input_data, decoder_target_data, sample_ind, enc_tail_len=50):\n",
    "\n",
    "    encode_series = encoder_input_data[sample_ind:sample_ind+1,:,:] \n",
    "    pred_series = predict_sequence(encode_series)\n",
    "    \n",
    "    encode_series = encode_series.reshape(-1,1)\n",
    "    pred_series = pred_series.reshape(-1,1)   \n",
    "    target_series = decoder_target_data[sample_ind,:,:1].reshape(-1,1) \n",
    "    \n",
    "    encode_series_tail = np.concatenate([encode_series[-enc_tail_len:],target_series[:1]])\n",
    "    x_encode = encode_series_tail.shape[0]\n",
    "    \n",
    "    plt.figure(figsize=(10,6))   \n",
    "    \n",
    "    plt.plot(range(1,x_encode+1),encode_series_tail)\n",
    "    plt.plot(range(x_encode,x_encode+pred_steps),target_series,color='orange')\n",
    "    plt.plot(range(x_encode,x_encode+pred_steps),pred_series,color='teal',linestyle='--')\n",
    "    \n",
    "    plt.title('Encoder Series Tail of Length %d, Target Series, and Predictions' % enc_tail_len)\n",
    "    plt.legend(['Encoding Series','Target Series','Predictions'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generating some plots as below, we can see that our longer time horizon predictions (60 days) are often strong and expressive. Our full-fledged model is able to effectively capture weekly seasonality patterns and long term trends, and does a very nice job adapting to the varying levels of fluctuation in each series.   \n",
    "\n",
    "Still, we can do even better! We'd benefit from increasing the sample size for training and fine-tuning our hyperparameters, but also by giving the model access to additional relevant information. So far we've only fed the model raw time series data, but it can likely benefit from the inclusion of **exogenous variables** such as the day of the week and the language of the webpage corresponding to each series. To see how these exogenous variables can be incorporated directly into the model **check out the next notebook in this series**. \n",
    "\n",
    "If you're interested in digging even deeper into state of the art WaveNet style architectures, I also highly recommend checking out [Sean Vasquez's model](https://github.com/sjvasquez/web-traffic-forecasting) that was designed for this data set. He implements a customized seq2seq WaveNet architecture in tensorflow.    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uRqWoHqHmTez6TJgb9xwLIYQQopQkCHNzFqsdHZCZYyM9y1rZ1RFCCCGEi0gQ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\nEQL/D4c5iCg+FjrKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2ef3fda0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict_and_plot(encoder_input_data, decoder_target_data, \n",
    "                 sample_ind=16534, enc_tail_len=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5k4w6w0ltfO0s7y+pq/n9X758hlq16l2VcxXHtb5t0XffreeGG2rTvPkdXL58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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2f3b89b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict_and_plot(encoder_input_data, decoder_target_data, \n",
    "                 sample_ind=16555, enc_tail_len=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0Ez179izzyYQQled8QiYxSVmM7hvJV5kWLiRkeXpIQoirRKNG1/Hqq/NxOOxo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\nIwZSRERERDliIEVERESUo/8Hgg7h42t4k1MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2f9a3668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict_and_plot(encoder_input_data, decoder_target_data, \n",
    "                 sample_ind=4000, enc_tail_len=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Zm/Fe0Wg0mfqRsf+KojBp0iQCAgIASExMzPP6hISEsHXrVkaNGkVgYCCBgYGMGjWK/v37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\nUCgU48D/DzJM+BP1uzZBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2ebadf28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict_and_plot(encoder_input_data, decoder_target_data, \n",
    "                 sample_ind=68000, enc_tail_len=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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c+x8Vl4aPvzqAV9rVQKemT9j9+MW9/47G/pfc/pfkvgPO7/+dO9dQvnxVp53v\nUYrzrXL++9+tqFChIp59tj7u3LmD4cPfwI8/blKClD3Yu/9Z31+NRoK/v1f+21XQBjRo0AANGjRQ\nvn/55Zfx999/5zlgFaSxeREQ4O2Q4z4uinP/M+59/j08XB3WzuLcf2dg/0tu/0ty3wHn9j86WgOd\nrnjdCKW4tcemevXqmD17OmRZvleNGgdXV/tfX2fP/ms0Grt8ngrcy8OHD8NkMqF5c+vVCUIIZbJ7\nXrCCZX/Fvf+xsSkAgKTkDIe0s7j339HY/5Lb/5Lcd8D5/ZdluVhVjIpzBatmzafxzTffZ9pm77ba\nu/+yLGf6PBW0glXgyJecnIw5c+bAYDAgJSUFGzduxIsvvljQw1EJYLFNci/YqDQREdFjo8AVrHbt\n2uHEiRPo3r07ZFnGa6+9lmnIkCgrW67iVYRERKR2hRoIDQ8PR3h4uL3aQirHqwiJiKikKJ6z4kiV\nbEOEBbxwlYiI6LHBgEVOYxsatLCERUREKsd7EZLT2CpXnINFRGQf8+bNxqlTJ2AymXDjRqSyCGiv\nXr0REtLVIee8cSMSq1evzHGhzr/++gOrV/8fLBYLAIGXXgpF7955X4TcYrHgjTfCsHz5949+cjHH\ngEVOw6sIiYjs6/33P4JOp0Fk5A0MHz7soTd9tpfbt2/h1q1b2bbfuXMHS5cuwvLl36NUKR+kpaXi\n7beHomrVJ9G8eXCejq3ValURrgAGLHIiW7ASxXO5FiIiVYmKuoPZs6chOTkZcXGxCAnpisGD38Cv\nv27C9u2/IyEhHq1bt0NoaHdMnToBKSnJqFGjJo4dO4qff96CtLRUzJs3G1evXoEQMvr1G4QXXngR\nn38+F1FRUfjss08z3Y4nISFeuY9hqVI+8PDwxIQJU+Dm5gYAOH36FBYtmg+DwYDSpX0xevQ4lC9f\nAW+9NQR+fn64cuUypk2bg8GD++Lvvw/mev4LF87h009nQpZl6PV6fPLJFJQrV7GoXuZcMWCR09hu\nqM4KFhGphf7WGrjdWuWQY2dU7AdDxdce/cRc/PHH7+jYsTM6duyMpKQk/Oc/oXj55d4ArPcv/P77\nddBqtRgzZhQ6dHgJ3br1xI4df+LPP/8AAHz77deoW/cZTJgwBSkpKXjzzcGoW7ce3nvvA6xatTLb\nvQ6ffro2mjZtjl69uiIw8Gk0bNgIHTq8hEqVKsNoNGLOnGn49NPPUbZsOezbtwdz5szA/PlfAABq\n1qyF6dMVbpITAAAgAElEQVQ/hdlsVo6X2/l//HE1+vULQ5s27fDbb7/g1Kl/GLCoZOMkdyIi5+nX\nbyCOHInAmjX/h6tXr8BsNsFgyAAA1KpVG1qtFgBw+PAhTJo0AwDw/PPtMWfOdGW72WzC5s0bAQAZ\nGem4evXKQ+/a8tFH4zFo0FAcOrQfhw4dxNChAzFlygyUK1cet27dxOjRIwFY5+QaDAZlv7p162U7\nVm7nb948GHPnzsT+/XvQsmUrtGnTVvkFvjhhwCKnub8OFgMWEamDoeJrhaoyOdLnn89DTEwU2rfv\niDZtnsfBg/uVi430er3yPI1Gm+PyObJswaRJM1CjRk0AQFxcLEqV8sGxY0dyPN+ePbtgMhnRrl17\nhIZ2R2hod2zcuAG//fYLwsKGokqVJ/Dtt6sBWCezx8fHK/u6urrl+fw6nQ7PPlsfe/fuxtq1q3Do\n0AG8//6YAr5KjsNlGshpbBUswQoWEZHDHT58EH37DkS7du1x9eplxMXFQs6h1BMU1Bjbt/8OwBqS\n0tPTAAANGzbGpk0bAAAxMdEYMKA37t6NgVarhcViznYcvd4VS5cuwp07dwBY7+l36dIF1KxZC9Wq\nVUNsbCz++ecEAGDz5o2YOnXiQ9uf2/nHjfsQFy9eQI8eL2PIkGE4f/5cAV8hx2IFi5yGFSwiIufp\n338QJk0aB71ej3LlyiMwsBZu3bqZ7XkjR36I6dMnYePG9ahZsxY8PDwBAK+//ibmzp2JAQNehSzL\nGD58JMqXrwC93g0JCQmYPn0Sxo2bpBynceNm6N9/ED78cAQsFguEEGjWrCUGDhwCnU6HKVNm4fPP\n58FkMsLLyzvTvjnJ7fwDBw7B7NnT8c03S+DqqseHHxa/6hUASKKIltWOjU2x+3pIvKN88e7/gdN3\n8NWvZ9Ckdlm82S37eHthFff+Oxr7X3L7X5L7Dji//3fuXEP58lWddr5H0ek0MJsLPglp3bo1aNas\nBZ544kmcOXMKCxZ8iq+/XmnHFjpWYfufVdb3V6OR4O/vlf922a1FRI9wfx2sIm4IEREpKlWqggkT\nPoZGI0Gvd8Po0WOLukmqwIBFTnN/HSwmLCKi4qJly1Zo2bJVUTdDdTjJnZzGNhjNOVhERKR2DFjk\nNMoQIStYRESkcgxY5DTKQqOsYBERkcoxYJHTcA4WERGVFAxY5DQyryIkIrK7W7duoW3bZggLew2D\nBr2Gfv1eQXj424iOjirQ8bZu/RXTp08CAHzwwQjcvRuT63OXL1+GEyeOAQBmzZqKc+fOFOicasSA\nRU6jLDTKhEVEZFdlygTgu+/WYMWKNVi1ah2eeqomvvzy80Ifd+7chShTJiDXx48dOwKLxQIAGDNm\nAp5+uk6hz6kWXKaBnOZ+BYsBi4jIkRo2bIRlyxbh5Ze7oE6derh48TwWL/4GBw7sw/r1ayHLArVq\nPY1Roz6CXq/H779vwcqVy+Hp6YXy5cvD3d0DAPDyy13wxRfL4Ofnj/nzZ+PkyePQ6XQIC3sdRqMR\n58+fxezZ0zBjxlwsWDAHgwe/gYYNG+H//u9b/PHHNmg0GjRu3Axvvz0C0dFRGDv2A1Sv/hQuXDgP\nPz9/TJ06Cx4enpg5czKuXLkMAOjRoxe6du1RlC+fXTBgkdPIvIqQiFSo+6Z12bZ1rRGIwfXqI81k\nwmtbNmZ7vPfTddH76bqITU/HkP/+mu3xsLrPoXvNWgVqj9lsxs6df6Fu3WcREXEAzZq1wJQpM3Hl\nymX8+usmLFnyLfR6PZYuXYS1a79HaGg3LFmyECtWrEGpUj4YPTpcCVg2P/30I9LT07F69QbEx8fh\nvffexooVq7Fly2YMHvwGnnqqhvLc/fv3Ys+eXfjmm++h0+kwfvxobNr0E1q0CMalSxfx8ccTERj4\nNMaN+xB//LENTz1VE0lJSVixYg3u3o3BkiVfMGAR5YfMdbCIiBzi7t0YhIW9BgAwmYyoXbsu3nrr\nXUREHECdOtZbkx07dhg3bkRi2LBBAACz2YTAwKfxzz8nUK/es/Dz8wcAdOjwEo4cich0/OPHj6Jr\n1x7QaDTw9y+DVauyh0qbI0ci0L59R7i5uQEAQkK6Ytu2LWjRIhi+vn4IDHwaAFC9eg0kJSWhevWn\ncP36NYwa9S6aNWuJd955z74vThFhwCKnuV/BKuKGEBHZ0abur+T6mIeLy0Mf93d3f+jjeWWbg5UT\nvV4PALBYZDz/fHuEh38IAEhLS4PFYsGRI4fw4O+9Wq022zG0Wh0ASfn+xo1IlCtXPsfzCSFn+R6w\nWMwAAFdX1yyPCfj4lMb3369DRMRB7N+/F4MH98P336+Dt7f3wztdzHGSOzmNMsmdFSwiIqdr0CAI\nu3btRHx8HIQQmDdvJtatW4Nnn62P06dPIiYmGrIsY8eO7dn2rV+/AXbs2A4hBOLj4/Duu2/AZDJC\nq9Upk9xtGjZsjD///C8MhgyYzWZs3boZDRs2yrVde/b8jalTJ6JFi2CEh38Ad3f3Al8BWZywgkVO\nw0nuRERFp2bNQAwaNBQjRrwJIQRq1AhEv35h0Ov1CA//EOHhb8PNzR1PPlkt2749evTCZ599irCw\nPgCAkSM/hIeHJ5o2bY65c2di/PjJynNbtmyFixfPY8iQAbBYzGjSpBn+859XERMTnWO7mjVriZ07\nd6B//1fg6uqKjh07Z5rT9biShCian3axsSl2n+wcEOCNmJhkux7zcVLc+//jjov476FIVPD3wPSh\nzex+/OLef0dj/0tu/0ty3wHn9//OnWsoX76q0873KDqdBmZzyZ17Ye/+Z31/NRoJ/v5e+T4OhwjJ\naXgvQiIiKikYsMhpbPMeOURIRERqx4BFTnN/JfcibggREZGDMWCR01g4yZ2IVKKIpi+Tg1mXmJAe\n+by8YMAip+G9CIlIDXQ6V6SmJjFkqYgQAmazCQkJd+Hq6maXY3KZBnIawQoWEamAr28A4uNjkJKS\nUNRNAQBoNBrIJXjuhb36r9Fo4e7uBS8vHzu0igGLnMjCChYRqYBWq0OZMhWKuhkKLtNRPPvPIUJy\nmvsLjRZxQ4iIiByMAYuchjd7JiKikoIBi5xG5kKjRERUQjBgkdMwYBERUUnBgEVOoyzTwCFCIiJS\nOQYschpb5UoILtJHRETqxoBFTvNg5Yr5ioiI1IwBi5zmwblXFs7DIiIiFbNLwJo9ezbGjBljj0OR\nij0YsDgPi4iI1KzQAWv//v3YuHGjPdpCKvdg0YpXEhIRkZoVKmAlJCRgwYIFePPNN+3VHlKxB4cF\nOcmdiIjUrFABa+LEiRg5ciRKlSplr/aQij04LMgCFhERqVmBb/a8fv16VKhQAc2bN8fPP/+c7/39\n/b0KeuqHCgjwdshxHxfFuf9azf08X9rXA77ebnY/R3HuvzOw/yW3/yW57wD7z/4Xv/4XOGBt3boV\nMTEx6NatGxITE5GWloYZM2Zg7Nixedo/NjbF7vNwiusdtZ2luPffYDIrX8fEpMCcYbLr8Yt7/x2N\n/S+5/S/JfQfYf/bfsf3XaKQCFYUKHLBWrFihfP3zzz/j0KFDeQ5XVDLJnINFREQlBNfBIqfhVYRE\nRFRSFLiC9aCePXuiZ8+e9jgUqZgsy/e/ZgWLiIhUjBUschpZBrQaCQBXciciInVjwCKnkYWATqu5\n93URN4aIiMiBGLDIaWRZQKe1VrAEExYREakYAxY5TeYKFgMWERGpFwMWOY21gsWARURE6seARU4j\nCwGdzvqR4yR3IiJSMwYschpZxgNzsIq4MURERA7EgEVOIwsBnYZDhEREpH4MWOQ0siyg00nK10RE\nRGrFgEVOI8sCLpzkTkREJQADFjmFLAQEAK0tYLGCRUREKsaARU5hC1SsYBERUUnAgEVOIe4FKq3W\nNgerKFtDRETkWAxY5BS2QMUKFhERlQQMWOQUtoVFdZyDRUREJQADFjmFrWJlW2iUFSwiIlIzBixy\nClmZg8UKFhERqR8DFjkFryIkIqKShAGLnMIWsHgVIRERlQQMWOQUtooVK1hERFQSMGCRU9gqWDod\n52AREZH6MWCRU9jylE7DqwiJiEj9GLDIKe7PwWIFi4iI1I8Bi5xCuYrQNkTIfEVERCrGgEVOkW2h\nUSYsIiJSMQYscor7AYtXERIRkfoxYJFT8F6ERERUkjBgkVOIewuL8l6ERERUEjBgkVNY7i3dzqsI\niYioJGDAIqew5SmtJEGSWMEiIiJ1Y8Aip7AFKo1GgkaSeC9CIiJSNQYscgrbkKBGI0GjkVjBIiIi\nVWPAIqdQApZ0L2BxDhYREakYAxY5ha1ipbUNEbKCRUREKsaARU5hq1hJEqCReBUhERGpGwMWOYUt\nT92fg1W07SEiInIkBixyClvFShkiZMIiIiIVY8Aip8g2yZ1zsIiISMUYsMgpbIFKulfBEqxgERGR\nijFgkVMoQ4SSBI0GsLCCRUREKsaARU5hybaSOwMWERGpV6EC1ueff47OnTsjJCQEK1assFebSIWE\nMgcLvIqQiIhUT1fQHQ8dOoQDBw5g8+bNMJvN6Ny5M9q0aYPq1avbs32kElmXaeAcLCIiUrMCV7Ca\nNGmC//u//4NOp0NsbCwsFgs8PDzs2TZSEYucZYiQc7CIiEjFCjVE6OLigoULFyIkJATNmzdHuXLl\n7NUuUplMyzRIkhK4iIiI1EgSovClhPT0dLz55pvo3LkzXn31VXu0i1Tmpx0X8d2WM1g/MwRjF++F\nt6crJg9tXtTNIiIicogCz8G6fPkyjEYjateuDXd3d3To0AHnz5/P8/6xsSl2v5IsIMAbMTHJdj3m\n46Q49z8pOQMAEBebCtkiw5Bhsntbi3P/nYH9L7n9L8l9B9h/9t+x/ddoJPj7e+V/v4Ke8MaNGxg/\nfjyMRiOMRiP++usvBAUFFfRwpHKyskwDryIkIiL1K3AFq02bNjh58iS6d+8OrVaLDh06ICQkxJ5t\nIxXJOgeL62AREZGaFThgAcDw4cMxfPhwe7WFVEwWApIESPfuRWiyyEXdJCIiIofhSu7kFLJsrV4B\n1sVGuQ4WERGpGQMWOYUsBLQaa8CSNFwHi4iI1I0Bi5xClgWkewFLK0mQOUJIREQqxoBFTiHL4v4Q\nIStYRESkcgxY5BQPDhHyKkIiIlI7BixyCmsFy/o152AREZHaMWCRU8ji/hwsjQRWsIiISNUYsMgp\nZBnKEKGWFSwiIlI5BixyCsuDk9x5FSEREakcAxY5hRACGq6DRUREJQQDFjlF9goWAxYREakXAxY5\nhfxABYvrYBERkdoxYJFTPLjQqJYVLCIiUjkGLHIKWRbQ3Pu0SRqwgkVERKrGgEVOIQvwKkIiIiox\nGLDIKTLdKodzsIiISOUYsMgpZPnBldw5B4uIiNSNAYuc4sFJ7qxgERGR2jFgkVNkGiKUACGsi48S\nERGpEQMWOYW1gmX92rYeFqtYRESkVgxY5BSyyDwHCwCvJCQiItViwCKnkGXrAqMAlKFCVrCIiEit\nGLDIKSzyAzd7VipYDFhERKRODFjkFEJkvooQYAWLiIjUiwGLnCLTzZ7vTXZnBYuIiNSKAYuc4sEh\nwvsVrKJsERERkeMwYJFT5LhMAxMWERGpFAMWOYXINEQoKduIiIjUiAGLnMLy4K1y7v1tYQWLiIhU\nigGLnEIWeGAOlm0bAxYREakTAxY5hSxnHyLkHCwiIlIrBixyClnOaR2somwRERGR4zBgkVPIIvsc\nLMGERUREKsWARU4hC6Hcg9BWweIkdyIiUisGLHIKWRaQ7n3alDlYnOROREQqxYBFTiHLeKCCdW8b\nAxYREakUAxY5nBAi8xwsjW0OVlG2ioiIyHEYsMjhbIWqrJPcWcEiIiK1YsAih7MFqazrYHGSOxER\nqRUDFjmcbUFRjSbrOlgMWEREpE4MWORwtkoV18EiIqKSQleYnRctWoRt27YBANq0aYPRo0fbpVGk\nLiLrECErWEREpHIFrmDt27cPe/bswcaNG7Fp0yacPn0a27dvt2fbSCXuV7Cs3yvLNPAqQiIiUqkC\nV7ACAgIwZswYuLq6AgCeeuop3Lp1y24NI/WwjQRykjsREZUUBQ5YNWvWVL7+999/sW3bNqxdu9Yu\njSJ1yTbJ3TYHi0OERESkUoWagwUAFy9exLBhwzB69Gg8+eSTed7P39+rsKfOUUCAt0OO+7gojv0X\nOi0AwKeUOwICvJFusQYrLy83u7e3OPbfmdj/ktv/ktx3gP1n/4tf/wsVsI4cOYIRI0Zg7NixCAkJ\nyde+sbEpSmXDXgICvBETk2zXYz5Oimv/7yakAwBSUwyIiUlGYqL1+4TENLu2t7j231nY/5Lb/5Lc\nd4D9Z/8d23+NRipQUajAAev27dt45513sGDBAjRv3rygh6ESwHa1oHIvQinzdiIiIrUpcMBavnw5\nDAYDZs2apWzr3bs3+vTpY5eGkXrYKpXSvasHOcmdiIjUrsABa/z48Rg/frw920IqJWddaNR2s2fm\nKyIiUimu5E4OZytU2YYIJdvNnlnBIiIilWLAIofLWsHSciV3IiJSOQYscjhbkJKy3iqHFSwiIlIp\nBixyOFuQynYVIQMWERGpFAMWOZwlyxChMgeL+YqIiFSKAYscznZLnPs3e+YcLCIiUjcGLHK4rPci\n1HIOFhERqRwDFjmcReR8s2dWsIiISK0YsMjhZNn69/05WLbtDFhERKRODFjkcHKWCpYkSZAkVrCI\niEi9GLDI4bIuNApY52HZKltERERqw4BFDpd1HSzAGrZYwSIiIrViwCKHy7qSu+1rzsEiIiK1YsAi\nh7s/RHh/m0ZiwCIiIvViwCKHs1WwMg8RcpI7ERGpFwMWOVzWZRqAe5Pcma+IiEilGLDI4bIu0wBw\nDhYREakbAxY5XNZb5QCcg0VEROrGgEUOp1SwJC7TQEREJQMDFjmcJacKloaT3ImISL0YsMjhRA4r\nuWs0Gg4REhGRajFgkcPZcpTmgU+bdZmGomkPERGRozFgkcNZ7q3TkLmCxUnuRESkXgxY5HD3K1i8\nipCIiEoGBixyuFyXaeAkdyIiUikGLHI4OcdJ7gxYRESkXgxY5HCyEJnuQwhYJ7wLDhESEZFKMWCR\nw8mygCRlCViSpKyPRUREpDYMWORwshCZlmgAbHOwiqY9REREjsaARQ4ny8hhiJBzsIiISL0YsMjh\nZFlkmuAOWAMW52AREZFaMWCRw8ki5zlYrGAREZFaMWCRw+V4FaEETnInIiLVYsAih7PIItMio4Dt\nVjlF1CAiIiIHY8AihxOyQJZ8BY0kQXCIkIiIVIoBixzOukwDryIkIqKSgwGLHM6Sy1WEvNkzERGp\nFQMWOZwskL2CxUnuRESkYgxY5HAip0nunINFREQqxoBFDpfTEKGk4a1yiIhIvRiwyOFymuSu5Rws\nIiJSsUIHrJSUFISGhuLGjRv2aA+pkCxymOTOldyJiEjFChWwTpw4gT59+uDff/+1U3NIjWRZQJPl\nk6aRWMEiIiL1KlTAWrduHT755BOULVvWXu0hFZJlAW22OVhgBYuIiFRLV5idp0+fXuB9/f29CnPq\nXAUEeDvkuI+L4th/rU4LF0nK1DYvTz2EsH97i2P/nYn9L7n9L8l9B9h/9r/49b9QAaswYmNT7D5E\nFBDgjZiYZLse83FSXPtvMJjhotNkapshwwSLLOza3uLaf2dh/0tu/0ty3wH2n/13bP81GqlARSFe\nRUgOJwsBbY43e+YQIRERqRMDFjmcnMNCoxInuRMRkYoxYJHDyTndi1ACBMDV3ImISJXsMgdrx44d\n9jgMqVRuC43aHst6hSEREdHjjhUscjhZWCtWD7IFLlkuggYRERE5GAMWOZwll5s9A1wLi4iI1IkB\nixxO5DLJHQAnuhMRkSoxYJHD5XgvQg0rWGR/QghMXXkYu07cKuqmEFEJx4BFDmfJ4SpCZZI7K1hk\nR9Hx6bh6OwlXbiUWdVOIqIRjwCKHy+kqQtu3zFdkT5fvBauUdLPdj33pRiKOnI+2+3FLJCEAwStc\nSN0YsMjhcpyDxQoWOcDlW0kAgJQ0o12Pe+xCDOasPYqlv5xGfLLBrscuibzOfwifI12KuhlEDsWA\nRQ5nHSLMvE3DSe7kAJdvWitYyekmux0z4lw0Fm86hfJ+npCFwI6jN+x27JJKl3AArvG7oTHcKeqm\nEDkMAxY5nCzAZRrI4TIMZtyITgUApNgpYB04cwdLfzmF6hVL4eN+DdGgZgB2HrsJg8lil+OXSEJA\nl3oJAOAS+1cRN4bIcRiwyOFyulWOllcRkp1dvJEAWQg8UdYLqenmQn+2LLKMNdsvonrFUhj1Sn24\n63V4sVFlpGaYsf80Ky8FpTHcgiSnAQBc7/5ZxK0hchwGLHK4nCa5S/c+eRwiJHs5fy0eAPBsDX/I\nQiDdULiJ7ueuJyAl3YROTapC76oFAARWKY2q5byxPSKS99EsIG2atXplcXsCrnE7AMFqIKkTAxY5\nnCwLpWJlc3+IsChaRGp0/locyvm6o4KfJwAgJa1ww4QRZ6Ohd9Ximep+yjZJkvBi48q4HZuG01fj\nCnX8kkqbehEAkF7lDWhM8dAlHS3iFhE5BgMWOZwsC2XldhtOcid7EkLg3LV4VK/oA093FwCFm+hu\nkWUcvRCD+jXKwNVFm+mxJrXLwcfTFX8cjixUm0sqbdolCI0HMir2hYDEYUJSLQYscighBAQedrNn\nBiwqvNjEDCQkG1CjUil4e1gDVmEmup+7Zh0ebFSrbLbHdFoN2tSviFNX4vJ1DqPJUuhhSzXQpl6E\n2bMGhKs/zD5BcI1lwCJ1YsAih7JNNM42RMhJ7mRHtvWvqlf0gde9ClZhhggjzmUfHnxQ5QAvAEBc\nUkaej7ny93OY/+PxArdJLXRpl2DxqAEAMPq3hy7xCCRjbOEOakyEZIqHZIoHLOl2aCVR4TFgkUPZ\nKlRcpoEc6fLNROhdtahc1vN+wCpgBctsyX140Ma3lB4A8rzoqCwE/rkSh2tRybDIJXgFc9kITfq1\nTAFLggzXuJ0FPqT79SXAhtIos7Oq8keT8fC1ynQJB6FL5NwvciwGLHIo28+SbAHr3iePd8sge7h8\nKwk1q5SGVqOBm6sWWo1U4IB1/t7Vg42fzj48aOPn7QYAiMtjwLp9NxUp6SaYLQJ3E/Ne9VIbbdpV\nSJBh8bQGLLNPEGRd6RyHCbUp5+F1ZgQ0aVcfekxd4hFAH4CUWrOQWm00JDkDLvF7ct9BNsLnxGvw\nOjeyUH0hehQGLHIoW4Uq6zpYtu9L9G/zZBcmswXXo5JR6wlfANYr/bw8XJCSXrDb5USci4LeVYt6\n1XIeHgQAH09XaCQJ8cl5C0sXIhOUr2/HphWoXWqgLNHgUdO6QdLC6P88XGO2wu3m99ahQks6PC5N\nhe+BFnC/+R300b88/JgZ1wGfukh/4m2kPfUxZK0XXBIjcn2+a8wWaIwx0CWfBmT73lKJ6EG6om4A\nqZtFfnjA4hx3KqzI6FRYZIFaVX2Vbd7uLkguwBwsWQgcvXD3ocODgLUiW9rbFfFJeatgnY9MgKeb\nDqkZZtyJTQNq5LtpqqBNsy7RYBsiBID0qu/AJTEC3mfegRc0EC5+0JjuIqNCb7jGbIM2/dpDj6lJ\nvw74dbB+I2lh9gmCLiH3gOV+41vrU4URupQzMJeqX8heEeWMFSxyKKWCxUnu5CDXo5MBANUrlVa2\nebm7FGiIMDHFiJR0EwIr+zzyub7e+jwNEQohcD4yAfWq+6OUpytux6bmu11qoU29BNm1LITL/dfX\n7NMYccGnEN90F9KqvQ9T6SZIaLgZyfW+gsW9KjQZD1kOQzZAY7gNeD6pbDL5NIYu5R/Akr1SqE29\nBNe4v5FesR8AQJfEiw7IcRiwyKFEbpPc730vWMKiQoqMSoG7Xoeyvu7KtoIGrOh46w/lgAeOlRtf\nb7c8TXKPTkhHYooRgVVKo4KfR4keItSlXYTZI4fynSTBXKo+0mpMQFL9H2DybwsAkN2qQJuee8DS\nZNyABJEpYJl9GkMSFrgkHcv2fLeb30FIOqQ9NQGyrjR0OTyHyF4YsMih7g8RZt5+fw4WAxYVzvXo\nZDxR1ivTYrZeHq4FC1gJ1kv8y5Z+dMDy89YjPtnwyFvmnL9unX9Vq0ppVPD3wO3Y1MfmNju6xCOQ\nzMl2O5427RIsnjXz/HyLWxVrBSuX10ubft36RZYKFgDoss7DsmTA7dYqGAM6Q3arAHOp51jBKmb0\nt9bC/er8om6G3TBgkUPlPkSY+XGigpBlgcjoFFQp55Vpu62Cld/PV0xCOjSSBL9Sbo98rq+3HoY8\nLB56ITIBXu4uqODvgfL+nkjNMBdqlXmnsaSidEQHeF6YYJfDSaYEaIwxmeZfPYrs/gQ0lhRIppxv\nS6QELK8nlW3CtQzM7tXhknAo03P10ZuhMcUhvfJgAIDZuz50KXmc6C4EPC+Mzx7a7EyXeBjep4bB\n7cbKRy41kV/a1Eu5BtXiwu32WnhcW1TUzbAbBixyKFuBKtdJ7ryIkAohKj4NRpOMJ8p6Z9ru5e4C\nIYC0jPytnB4dnw5/Hz102kf/1+jrbV0LK+4RE90vRCagVpXSkCQJFfw9AMA60b2Y06VehCRM0N9Z\nB5hTCn28+1cQ5j1gWdyesO6byzwsTcY1CEkLuFfKtN1curE1DD0QKNxufAuL+5Mw+bW1PqdUfWWi\n+6O4xO+Gx7WF8Dr/cZ7bXhCelybD7fZaeJ8dDv/ddVD6YNvCL8IKQJN2Bb77guD6iCsyi5rGcBsa\n013rgrEqwIBFdnc9Khk//X0ZQojcFxq1zcEq5r9RUfEWGW39wf9ElgqW973FRlPzWSmKSUjP0/Ag\nkLe1sGITM3A3MQOBT1gn4Ffwswasx2Giuzb1AgBAY0mB252fCn88W8DKxxCh7F7F2oZcApY2/Tpk\nfWVAk/mCeJNPE2iNUcp+LnF74JqwD+mVhwKS9ceeqVQDAHmb6O5278pDl8RD0CUczHP780Obcg6u\ncYnEdM8AACAASURBVH8jpcYniGt+AKnVx8Il6Shc7/5e6GPrkv+BBPHQ5SuKA40hCsD9z8rjjgGL\n7O63ff9iy/5ruB6VogSsbLfK4UruZAfXo1Kg1UioWMYz03Yvj4Ld8Dk6Ph0Bvh55eq6fspp77mth\n2da/qlXFGrD8fNzgqtM8FhPdtannIaCB2TMQbjdX2OF4FyEkLSzuT+Z5H6WCZRsKzHrMjOuwuD+R\nbbv53jwsl8RD1uG9S5/Aoq+A9CqvK8+R3avlaaK7ZIiGPvpXpFcaCFlX2mFDWO43voaQXJFRaSAs\nXnWQVv0jyC5l4Br3d6GPrUs9b/07+VShj+UwlnRozNZ/L9rUi0XcGPtgwCK7SjeYcfKytaR95EJM\n7guNajjJnQrvenQyKpbxzDakV5D7EaZlmJCaYc5zBauUpysk6eG3yzkfmQB3vU65d6FGklDezwN3\n4pwQsISA7/5mcLu+tEC761IvwOJRDemVX4dL0lHokk4UqjnatMuwuFUFNK553ke4+EFoPaHJyDlg\nadKvQ84pYHnVg9C4Q5cYAdeYrXBJjEBa9Y8B7QPvrSTlaaK7261VkIQJ6VVHIKPyILhG/5rj6vKa\n9OsodaIv/HbXzXGJiIeRzEnQ31oLQ/meEK5llPYZ/VrDJW53oedOaZWA9U+xnYelMdxRvmYFiygH\nJy7dhdEso5SHC45djFEqWFK2OVjWv2UGLCqEyKgUPFHWK9v2gtyP0HYFYUAeA5ZOq4GPp+tDhwgv\n3khAzco+mYbIy9+7ktDRNBmR0KWcgf7uHwXaX5t6ARbPWjBUeBVC4wa3m9/df1DIgCV/t/zRpV5U\nbpGTZ5IES25LNdxbA8tW5cpEo4OpVEO4xB+A56XJMHvURMa9ta8e9MiJ7kKG+40VMPq2hsWzJtKr\nDAMkDdyvL36gHUa4X50Pv32NoY/+FdqMSKVilFf62z9AY0lBepU3Mm03+bWG1nAT2rTL+TpeVspw\nr+kuNMaoQh3LUR5sly6VAYsom0Nno+HrrUfnZlVxMyZV+U2dQ4Rkb4kpBiSmGlGlnHe2xwoUsOLv\nLdGQhzWwbB62FpbZIiMqLj3b/LAK/p64m5ABk9mS5/MUhC75H+vfScfyX7WQzfeWVAiEcPGFoVwP\n6G9bJ7u7Rv0C370NUeZ/leBztCfcIpdDMjzih7awQJt2ERaPwHz3Q1mqIQvbGlg5DREC1onuLsnH\noEs9h9QaE7PN0wIePdHdJfYvaDOuIePelYeyW0UYyr8M91uroMm4BffrS+C3tz68Lk2CsUx7JDT4\nGcD9QJMnQsA98muYSjWA2adRpodMvq2s7YjflffjZTu+DF3qBZi8n7O27d7norjRGG4DsL7frGAR\nZZGaYcI/V2LR+OmyaBgYAAA4fD4GwP1lGWzuT3J3ahNJRZQJ7jlUsNxctdBpJSTn436EMUoF69FL\nNNjY1sLKSVRcGmQhUME/8/ywCv4eEACi4tLzfJ6C0CWfBABoTLEPXw09B9r0q5CECWbPWgCA9MqD\noLEkw29/U/ic7A9oXJFe5XVo0y7D+9xI+O1rlGmIJ9vx0q5Ckv+fvbMOc+u89vW7txiGR8Ns5tgx\nQxyyHcd2uIEGm7Qpc2/TND3t6W1vc9KewmlKp23atA1Dw+AkdhzHEDPz2B4PM0oj3vv+sSUNSTMa\nMH/v8/SpI2k+fVu0117rt37LQ9A+YdDHoVgKtHmDffao3aaYC6P+nT9ptvb/iTPwZVwX/TEDCN0t\nlX9DMTrwZqyM3NZZ+FWkoIvUDVOwH3kIxZxP6/R/0z7tafypl6FKukEFWIaWj9G7jvTJXoHWcRk0\n5WBoHnqAJXsqkBQ33sybgHNXh6ULfX78KQu1jJ16/reYiwBLMGLsPNpAUFGZMzGT9GQLBRl29h5v\nBGJrsESJUDBUykMBVm8PLNBK0jaLYVAarLoWN4k2I2Zj/CNaUxJMNLdHL5WFhew5vQKsrFAnYfVp\nLhPqnftRJS2TN1jH8rDIOGjTMk6BpDn4Ey4BxU/HhMdpmbsJ17jHaF6wm5ZZ7yEH2jBXPtnPeoe1\ndezjB30cQXMBsr+lj+FpOMCKlcHypyzAnzQL57jHoNfvT5j+hO6ypwZj47t4cu7uoRsLJkzBnXs/\nvvQltMxcTeus1fjTrw79kZGgpRj9IAIsc/W/UAwpkQCoB5KEP/UyjM3rh3w1Gi5XBpJnEzTna2OE\nzkFkbx2qpMefPAdJcSN7qs72loaNCLAEI8bWQ/U4ks0UZWklmxljHfj82lVIH5uGfpzcvf5gRA8j\nEMSivK6DtEQzNrMh6v0JgxyX09ASv0VDmJREEx5fdLPRcAAVDqjCZKZakTj9Xlj6jn340peiSoao\nY2P6IyyKjpT0JInWWatpXrQfT969XeU2SSKQPBdf2tVap6ES/fXWOw9p69kGH2DFsmoIe2Apppyo\nf6caUmidvYZA8pzYi/cjdDfWv4akBvHk3NnnPufE39B+yXMEUub1uS9oGzeoDJa+bSf+5AU9Bfjd\n8KUuRvY3onMdinvN7oT3ErCNI2CffM5msGRvDYopK/KZCw8GP5+5KAIsp9tPUDhanlbaO30cKmth\n9oTMiKB9eqhMCP1ksKJclb287jg//OsW2lzxl3cEFx8V9c4++qbuDHYeYX2re1DlQehmNhqlTFjT\n1ElaohmTUdfjdpNBR1qSmZrT2Eko+VvRucvwJ80kYJ806AyW3nWEoDGrx1BmdJaYHYDu/M+h89Zg\nbHgz6v061yGC5nxUfV+93EDEsmqI5YE1WPxJc9B37OmjIzPVv0HANmFQvl2gZf10naWgxGFyG3Sh\n6ywlkDA59v5COqyh2jXoXEdRDKmaw33CZC1w6dagYK54AlP1s0NaeySRvbUoxsxII8SFoMO64AOs\n5nYP/+ePm3hv2+A0CLH4+9uHeGtz2YisdSGx44hmyTB7QmbktjyHLXLCipXB6j3sORBU2HygFl9A\n4cOdIzsqQnDh4PUFqW3qJD+K/irMYAIsfyBIa4c37g7CMGGz0WheWDWNLrLTo3tqne5OQr3zAABB\n+2QCidMHLXTXdR6NlAfjwZe+lKClCEvFX2Ls5zCBIWSvgIgNQ2+rhlgeWIPFm/UpJBTMtS9GbpN8\njRhaNuLNWDXo9QK2sUiqH527bMDH6p0HkVAJJEyJ+RjFUkDQUhSXDstY9wpJO2/qoV/Su44QDGnp\nAglTkNQg+lA2TPK3YD/6MJaKPw+49ulG9tWhmLJRjJkouoQLwgvrgg+wXll/Aq8vyKna4Q8sVVWV\nbYfreXPTqSENkr1QKa/r4JX1J8hz2MlzdOlNJEli+hgtixV7FmHPtfYeb8LlCZCSYGLtzip8/q5O\nq0BQYd3uKjo6RWbrbBBUFBrbzo3SbWWDExUoiNJBGMZuNdIRpwarodWDyuA6CEETuQO09BqXo6gq\ntc2dffRXYbJTbVQ3uvj3+hMcKW/BHxjZDHu4UyyQMJVA4nTkQCtyHCd8AFQ1ZNEwiI4/SYc77wGM\nLRvQdRzoeZ8S0NYbgsAdQDFmoErGPlYNsTywBkvQPg5/4gzM3bI4poa3kVDwZkYXx/e7Xuh1i6dM\nGC7XBeyxM1iglQkNLRtA7b/z1Ni0DmPTBz1mJupcRyLNCsHQ84Sf11zzLJLi6bdBIRqmmueRo1ln\nDAOtRJipWXNYR6PvViKUO0+SuOtTGJo3jOhznm4u6ADrVG0Hm/bXIsGIOCd3egN4fEG8/iAf7T7/\nBXgjwanaDn7x7C6MBpmv3DS5j9/VwinZZKRYcCT1LL3EsmnYtL+WRJuR+1dMwOn2s/lA1xf/tQ0n\n+ee7R/jf1w8Ie4ezwMd7avj+n7ecExcX1Y1a9ifXET2AAS2D5fLEN/A5rPnLSI7PxT1McjjA6lUi\nbG7z4AsoZKVFX2/e5EwKMxN4e/MpHntmF994fANNbYPzleoPfcc+FEM6iimLQOIlAHHrsGRvLXKg\nPXJSjhdPzl2osrlPFkvrSPQRGGKAhSQTNOf11GD154E1BDw5n0bv3BcJTI31rxM0FxK0x84sxaJL\nQxRPgLUPRZeAYoneCRnGn7IIOdAW6QyNRdhLylT3CqBl4mR/cyToC1qLUWWrdpyqGhkBJPtqBwze\nIs/hLidx/+ewnvzvuB4fF4oX2d+CYsrS9mkbjc7V5f1lKf8DpsbVJO1YgbX0/8bU+p1rXLABlqqq\nvPBhKTaLgQVTsyMt08Mh/ANoMur4YHvliF91nm+crGnnF8/uwmzU89CnZ5ARZcRIXoad//r8PJLs\nph63R3Nyd7r97CltZO7ETCYWplCYmcB72ypQVJVDZc28vfkUeQ4bB8taWL01urMzwK5jDTz9/iB8\naARxcaKmnUBQoaph+IN/h0t9qxtZkkhLjK2ZShjEwOeGkAeWY5AZLL1OJjGK2Wh1jA7CMEVZiTxy\nz0x++/VF3L10LG5vgFN1w8+yR/bVsU8rO0kSAftEVMkYtw4rHBgMKoMFqMY0PFm3YK55Dsnf2rXe\nMATuYRRLYQ+rhoE8sAaLN/NmVMmg7T3QjrFpnVYejNF92B+qIYmgMSsus1G9cz/BhMmR+Yix8Kcs\n0B7furXfx4Vn+ZnqXgv5X4U6CMPBsqQjkDARvXM/hpaNmj9W4gwkNYjsaxhwvwDGpjWh/187Yj47\n4QyaYsoGNHsK2VMOQTcEPZhrnsfrWIEn5y5sJ/+b5O3LRmQI9unmgg2w9p1o5tCpFlYtKKIkJxFf\nQInZTh0vjaEAa+W8QtpcPj45OLi06oXG/75+AKtZz0N3Th+0diWaBmvboTqCisr8yVlIksTS2fnU\nNHWyeX8tf3nzIJmpVh65eyaXjnPw749OcLKmPera63dXs2ZHZdTOLkF04hm6XdWgZY2qGs/+oOKG\nVjdpSaY+I3K6Mxiz0fpWNyaDjkRr9I7E/khJMNHcS4MV1ldlx8hghbGa9cyeqOkWw0anw0bxo3ce\nJJAwVftv2UggYTL6joGHGkO3DsJBZrAAPHkPICmdmOpfj9wW1vsMNiPWHc3NvSvAGsgDa7CoxjR8\n6csw1byAseFtJNU3pPJgmKBt7MAlQlVB13GgX4F7GMWUo2WeBijzyr56FH0iOm8V+rZtUd/LgH0K\n+o79mCv/iqJPxl34Fe1vQ0afA2Fs+gAAnecUsvtEXH8zEJEAy5gZ2u8YJFR07pOY6t9ADrTizv88\nzkm/p33K3zC0bcdc89yIPPfp5IIMsBRF5cUPS8lIsXDF9NzIBPuB2qIHclYOZ7AWTcshz2Fn9daK\nyIlJUVU8vovnhN7Y6qa+xc2y2QWkJw0uuIKuC8PuWcVN+2vJc9giwuVZ4zNISTDxt7cO4XT7+fx1\nkzAZddy3fDxJdiP/+9qBqEFUWSgTcC4EAucD+0808a3fb+SdLadiPkZR1YjtwLnwuja0ugcM6sMD\nn+MJsMLr9S5xx0M0s9GaJhd2i4EE68Bz92xmA1aTnoYR0rfpOo9pJbluJ25N6L47LvNGveuIVrYK\nZRMGQyBxBkFLEaa6V7v24zykzSDUx25IGAjFko/sq490vw3kgTUUPDmfRuerw3bsxwSNmQRCRqVD\nIRJg9XPhIrvLkIMdBOIpQ0oSQWtR/wGWqiJ76/Bm3oIqGTHVvaoN7JatKOa8yMMCCZORA62Y6l7F\nk3MHQUuJth9PHAGW4sPQtA5f6mIglMXqZz8E4/tMhzNvQXNXBgs0PzZz9T8JWorwp14GaNlGRZ+I\nboSCu9PJBRlguX0B2lw+br9qDHqdTFYoTd+fDuvDnZV8/bcb+s16NLZ5MBpkEiwGrpmTT3Wjiw17\na3hjUxnf+9NmvvH4BnaXNo748ZxJVFXlaEUrH++p7jercai8BYDxBclDeh5JkpAlKRJg1TZ3cry6\nnXmh7BVo5ZerL81DBW5ZPIrCkL+WzWzgwVWTaGhz886WnqXCVqeXNqcmgq+sP/ulrHMZRVV5fcNJ\nfv3CHlxuP6+sPxGzs625zYPXp12AVDecCwGWZ0DPqsEMfK5vcQ9a4B4mJcHUR+Re3dRJzgDZq+44\nUiyRMmU0vL4gdS2dlNd1RP7X5ozuIB/W6UQyWGiBjxxoQ9c58ElJ5zqmWRMMIdhEkvBmXI+heR2S\nv1nbj+vwkAxGuxOxagjpsPrzwHL5h6bP8aUvRTGkoPNW4ctYOWDZrj8CtrHIgTYkX33Mx0QE7nFk\nsACClv4DLCnQiqT6CNpG40u7ClP9a6HuzbE9jiXcsSih4Mm9PxJIy97qAfdgaN2KHOzAnf8gQXNh\nvwGWqeYZ0taPGXiMEl3ZM8WoabACoQDL2Pg+xuaPtDmS4WOQJIKWkrg+y2ebYRmIvPHGG/zxj38k\nEAhw7733cuedfQ3ZzgY2s4HffHVhROeTaNWuEGNNsPf5g7y+sQyPL0hDqztmZ1JTu4f0JO0qd/aE\nTF7+6AR/f0dzKB5fkIzVrOfxl/dy7zXjuWxadPO7cxW3N8DHe6r5aE91JBA16GXmTsqK+vgj5a3Y\nLQZy0mOLjAdCliFsT7Zpfw2SBHMn9ny+pbPzKclJZGx+z0BubH4yo3KTOFTWDJeVRG4v69YtWiEC\nrJi4vQH+9/UD7D3exLxJmdywqIQf/30b/3z3CN/99PQ+mZzKUNYqJ9122h3IB6LTE8Dp9g+cwQoF\nWAONy1EUlcY2N5eMTh/SflISTKEGmABmox5VValpdDFzfEbca2QkW6JqsP702n72nWjC7e2bXbea\n9PzyKwswGXr6bEnt+/BJFoLWLv8mf0jorm/fNeDAZZ3rCP7Uy+Pee2+8mTdgPfU/GBvewZt1KzrX\nMXzpS/s87lhLMy8eOUiNy4lFb+Ch2fNJs0R/T7usGiq0DjPnoageWL/c/gk/37qJHy9YzBemXTq4\njctGbc5gxV+GZM/QnXBJTu86it+UGfUxeuc+VGQC9onxrWkp0rywVDVq8BvOAinGTLyZ12NseId6\nl5OU3J6vfdA+CQBfykKC9nGgBlGR4yoRGps+0NzWUxfjS7sSU+1LmuBc7ltaNza+hxxox1L1JJ0l\nD/W7ruyrQ5V0qMbQd1BvJ2jKxlz9FCpyH7PXoLUYffueAfd7thlyiF5XV8evf/1rnnnmGV599VWe\nf/55SkvPHWOw7rYAkiSR3Y/vzMd7ayKmlk396LQa29wRUa1eJ/OZa8dz/cJi/uvzc/nup2fwvTtn\nMKk4lSffOcxrG07GpWsZLOv3VA8YOJysaeen/9wetwZJVVUef3kvz60txWrS85nl4ynOTuC5taVR\nBcKqqnKkvIXxBclDKqmEkSUJRVGpb+nk/W2VTBuVHjFuDKOTZcYVpER9nrF5yZTVduDtZuVwqrYD\nCSjItFNxDoix+6O60XVWysrtLh8/f2YXB042c9fSsXx25UQcyRY+dcUojlS0smFv3x/asLB95jgH\nHZ1+2vuxymjp8MYlLB8qXTMD48xgDVAibOnwEgiqgxa4h0lNDHthaRmljk4/Lk+gzwzC/nAkW2hq\n8/QYHeX1Bdl2qJ6CjARuuXwUD6yYwJdvnMJXbprCrVeMptMbYE+UjPm/TjQy5dSXePfUqchvUNA2\nHlU2Dyh0l/xt6Lw1BGzj+KSmiq01WlbDEwjwk80f89zhA+xtqMMdiP2aBhJnEDQXaCWqzhOhmYZ9\nM1gVHe08vmsbH1eW88yh/Vz5wr/4pCZ6d3bQrLm5Gxs/IGn7tZga3sKXdkWPx/x+13Ye27qJOdm5\nLMrVArLSlmb2NcTOIvWms+ibuEoewp9y2YCPrXHGbkrosmqILXTXd+wnaB0FuvgynUFLEVLQheSP\nXiUJdxAqpix8jmt5qGkpOSe+wRdP9nztVX0CHeN+jmvsz7QbJB2KKTOuAMvQ9AH+5Lmo+kR8aVci\nBzvQt23v+0BVxdD6CQDmyr8PaLoaNhntnmkLWscgoeBLvxrFnNvj8YqlRGt6iMfM9Swy5ABr06ZN\nzJ07l+TkZKxWK8uWLePdd98dyb2NKFmp1qgZrEBQ4Z0tpyJi1P5apZvaPKR1sxuYXJzG9QuLI91z\nZqOer908lQVTsnhtw0kee2ZXpJ18JPD6gvzjncO8tO54v487dKqFE9XtnKiOLgLvzYa9NRwub+Xu\npWN55J6ZLJqWw93LxtHh8vHqx33TsA1tHpravYwvTBnScYSRZImAovDXtw4hyxJ3LR1c19LY/CSC\nisqJqrbIbadqO8hKszI6N4nKeudpCXJHgpomF//xxBa+/fuNPP3+0RH9nPRHY5ubR5/aQU2Ti6/e\nPJUrZ+RFgtdF03IYk5fECx+W0t7LRb+60UVqoonReZqzd39lwl88u4s/v3Eg5v3DJd4AKzzweaAA\nqzIUPA6mpNed8D4Olmll8/CF3GDWy0ixEFTUHo041U0uVODqmXlcO7eQBVOyuXScgxljHSydlU+S\n3cjWQ72CB1WlJHgIZBP3vPMaN732IsdamkE2EEiYiqE9ysmwG7rOY3gUPY8cT+H6V57nsW2btL24\nOvjTnh18be1qrn7xaYr/8jvufOuV6IGWJGkZlKa1GNq2AEQ8sBo6O/nRxo/wBgNclldA5ee/zu57\nH+Ttm2/HpNPxnXXvR526oZhyUCUd1vLfoXceoGPCb3FO+E3k/j9s28aPN6/n+lFjeeX6TzEpXfPf\n+9OenSx7+Rn+a+tGfMGBbQgUcx6dox7pkxlz+nx8dc27fH3tagCqOjpY8Ow/+PIH79Di6VvaVUw5\nKDp7v0J3fcd+as2X8L31a/juR2sit2+tiS7PUCxFgDY4OxqRDJYpk98fKOUXLfO53HKSyelaBs3l\n91Pr0j7rnoIvROw7tL/JRjdAiVD21mLo2IsvTZu76E+9DBUZY3PfMqHsOYXOW4Mv7Wp03mqMDW/1\nu7Yu7IHVjbAOy5N7b5/HB63FSGpg0EPMzzRDDrDq6+txOLpGoWRkZFBXN3Ct9WyRlWal1enrk9XZ\ntL+W5nZvRK/V3B5d1+D2BnB5AqQn9T9KQ6+Tuf/aCdy3fDxVDU5+9Let/Hv9CQLB4Vs6VDZq5ooH\ny5r7NdsM/0iX1Q4cYLW5fLzwYSlj85JYPL3rKqEoK5HLZ+SyZmdlH5PWI6e0E8m4guEFWDpJYvP+\nWkor27hzyZhIJiBeRucmIwFHK7sCrLLadoqyEsjLsOPxBSOdnwPxt7cO8fJH/QeuI8nmA9p3ZUpJ\nGh/truIHf93C2gGc60/WtPPDJ7ZwvLqt38fFQguudtLR6efbt1/C1FFpPe6XJYl7rhmPxxfsE1hX\nNbjITbeTm64JlWMJ3d3eALXNnew93nTanMrjDbAkSdLc3AfQYJVWtSFLEkXZiUPaz6icRMYXJPPK\n+hO0uXwRi4bBZrCAHjM4w12buY6+4nBZlpg1PoO9x5t6ZAtbmmq4xrSbd2dZeHTRlRxqbmT5y8+y\nvrIcf8oC9G07IBj7fWlvPcasis/x26Mt3D1xKv9YrnXSlSSlcOrBr7Hpjvt4YtlKvjBtBhuqKtgb\nIzvkzbgeSfVjKfsNKhIB2zicfh93vvUKTx7Yw7GWFvSyjC7kODzVkcmaW+/in8uvRyfLBBWlZ5Ah\n6/Fk34k79z6aF+zEk3dfJNvR7vXyfz/6iGuKRvGHq5dH1gR4ZO4Cbhoznl9t38KSF5/icPPgNbIN\nnZ3c8NoLvHT0EAlGrWnBYbXy4LTp/PvYYRY9908+ONXrQlSSCNrGdFk1BDuxHn8UnTM09NrbzO9r\ns5iyYyL/OLCXJFNX5v7Ot1/hU2+8TFlba48lg5ZigJg6LDmk93ruVDv/uWk9N+RaeT/3Ke6bro3a\nefdkKVP/8WeWv/wsj+/aRqun67dRMeUMaDZqaFrDYV86jzdoF8KqIYUT5gXoG/sGWOHslWv0Dwma\nC2I6/Ef27q2LaMHC77sv41p8aVfjS7+mz+O7Xovowea5wpA1WIqi9CjbqKo6qHJRWtrQO0r6w+GI\nrp8aV5wOH53Ao0BB6DHBoMK7W8sZk5/MFbMLeX5tKR3eQNQ1ToUsAYrzkmM+R3duvjqRq+YU8cQb\n+3lzUxlFucksmzu8luIdpZrvR1BROVLVzvL5xX0e43Ak4ArpNaqb3QPu9cl3t+P1K3zj05eSmdHz\nsQ/eOJVdRxt57sNSfv6VRZGya1m9k2S7iWnjM4dVItTpZDo6fcybks11l48Z0lrFOUmU1XXgcCTQ\n0u6h1elj0mgH4wpT4N0jtHuDTBzgNej0aIamRoPMZ66f0kfTEg/rd1WSlmRhUknagI8NTwS4ZIyD\n//jsPNqcXh7+w0b2nmjmtmWxzRif+uAYlQ0ufvvSXh77yiLyo2gFHY4EfvfibiwmPQ9c11M8u3p7\nJW0uH7/55mKKc5L6/G347xdNz2XHoTq+8elL0elkgkGFmuZOLp2YxZjiNGxmPc0uX9TP1pFTzZF/\nbzhQx5dunjbg6zFY2j0BEqxGCvP7Bvi995ScYMYXVPv9HpTXuyjJTSQvZ2gNGwBfv2MGX/3vdby6\noYwkuxGzUcfYkvQ+Ewxioeq0z5yn216bXacw6GUmjslAF2WdZfOL+WB7JcfrOijMT8HhSOCZD1x8\nWPkFbln2IN9Ly+DTl07lhueeIynJgjVzGZT9Goe6Fxx9NVEAj66rYr8vk9duvZnrJvQVX2dnJjGP\nQu4HfnjV5WTaY/yOp18JB/LRd5aCvYS0zAzue/ZZ9jXW8+rtt3PF2JI+f+IggRK05ovPvPYaiUYj\nv12+vOt34fJ/ANA7rHaQwMb77yc3MRGzXt/nvudv/xT3HD3KA6+/zm1v/pvNDzxAYXJ87/XJlhau\nf/0Fqtrbef2OO7h2TJeu7ZcrruHOGdO479VXueed1/ng7rtZXFTU9cepk6D+Ixz2TvhoFTRvw1b7\nFOrSLVz16qt82LCcJbmJ/Ob6u5gYSlaoqsr/u/JKHl6zhsXP/5MfX345X5szB5NeDymTYDMkStUQ\n5fNs17WAbOKgy81VxcU8d8cd6P13kGbVOgiX6cfwk6CHVw4f5iebP+b9ipN8dN99GHU6SC6AgNWQ\nWQAAIABJREFUto0xvyftXi+3Pn+c1U1fwVBRyr2XQabNxtwTV6L3NXGPbTPzi8YwOzcXm9EIJ3eA\nIZGU4vng/RK63d/DYayApBh6M38d+qwFOBwJXPv002ytqiLDZiMn4W4m79rKvLw8bpvc7fNomwo7\nIFnX9VrEc14+0ww5wMrKymL79q50c0NDAxkZ8Ys6m5qcPfQGI4HDkUBDQ/S6uFWvfUkPH28kxaId\n9qb9NdQ2dfKpy0fR2Ogk2W6kut4ZdY1jZVpwY5SI+RzRuPvqMWzZX8uB4w3MGJU62EPqwcHjjVhM\nOpLtJtZsLWfmmJ6i3PDx1zRqaeCjp5r73eve442s313FDQuLMcvRj+vmxSU88dYhXnjvMFddmoeq\nquw+2sCYvCQaG4encZIkrQHhtitGDXmt4uwEPt5bTU1tG5XN2tV/ut2ITS8hAQdKGxgVGggcCCp8\nsL2SxZfkYDF1ffR3HWsgqKi4vUHWflI2KHEyaCeE3724G7vFwKMPzhvwpFpa2UZdcyer5hdGXvPi\nrAR2HKmnvr49aqDp8wfZtLeaycWplNc7eeSPG3n4rhk9LDIcjgS276tm9SenMBt1XDs7v4dP1NYD\ntRRnJ2A3yP1+LibmJ7NuRyWbd1cyriCFmiYX/oBCqs1AY6OTrDQrxytao66x/5hmVjg2P5k128q5\ndnY+NvPgvaX6o6K2nfQkU5/nj/b9T7QaqKzviHm8gaDCkfJmFk3NGdT3ujcmCa6dW8DrG7UAKzPF\nSlNT/J9pVVHRyRLHK1poCGUWS8tbyE6z0hxjnVSLnrREMx9sKefKmQXsPlTLmh0VLJn5ORTFQkND\nBxZk3rnxDmRJoiFgQQ0mYj+5Gpd+XtQ1a1qbuSbBw7z0wgFfDxlocHfw3OEDGHU6bhrTU+tjS1+F\ntfwPeM3j+PWHH/P2sWM8uuhK5qRk97u2qqrY0PO7bdtwe/z8bOEVMS++Ov1+zHo9ozJSaWjoINaq\ns1OyeXHVzfxgwzqcbR4a/AO/106fj4XPPklnwM9L193CrOSsPvvO19t5ZdWnWP7ys/xr5x4m2rou\nsKz6EmydTxF8ZzayrwHXmJ9gO/4ope/ezp6GK/lF+nvct/QJVMw91r21eAILb8/je+vX8t0PPuC3\nn2xh3W33kGgykWrKxt90hI4on31PawUGYyY/nLkQbzBIe6sHSAKX9lg7ej4/YTqfnzCd10uP8tn3\n3uSht9/j+3MXYlXTsflaaKit14Z69+LPe7azusnOfxQ2ctsVj2DwQENnBw9PG8dfd67lB+s3w/rN\n6CSJuydO5S/Gj1ESZ9HW1ImUdBtp8o/w7Pk1zgm/6vtCKz7q2yHdl4rc0MFVuUVkmmw0ujupcrbz\n5x072FZRxZWZ3RIUagLpsgl3/SFcyR39nvtHAlmWhpQUGnKJcP78+WzevJnm5mbcbjfvvfcel102\nsDDwbJGRYkGWJGqau9Lj72+vJDfdxrRQ91BaojmmGWm41JQ2QImwN5IkkZNmpWYENDYV9U7yHXbm\nTMjkaEVrH++dMM3tXnSyRFO7t18x8kvrTpCdZmV5P5m1+ZOzmFySyovrSqlr6aSh1U1Lh3fI9gzd\n+dTlo/jqzVNJjMMrKBZj85Px+RVO1XVQWtkWEbibjXocKZYeDQHbDtXzwoelrOs15mj/yWaMBs2R\ne8vBwZe5G1rcuL1BGlo97Dw6sBvy5gO1GPVyZE4jQGGmHZcnEPM93Xu8CY8vyLI5BXzr1ml4fEF+\n+fyePu/vm5vLAPD4ghzrVjp1uv2U1bYzqWjgIH9ScSp6ncSuY1o5pfdYmtx0W0zNWHWjC6Ne5o6r\nxuDzK3y8Jz7zwsFQ3zKwB1aYwswEqhtdEYuJ3lQ2OPH5FUbnRs/oDYYV8wrJTLHQ5vTFHPIcC1mW\nSE8y97BqqGp0RUqy0ZAkidkTMzhY1kyb08ur609gMuhYMa/n9zls6vtc6SmKyr5OZe22aMsB8Mus\njfx7YvxlF0VVefbwfr6+djUVHT0lCd7MGwFwWibwq+1buLqgmPsnD5zRlCSJ/5x/GV+cdilP7NvN\n04f2x3zsL7ZtZuGzT8alrxqfms5L191ChtWGPxjEE+hfIG03Gvn39Z/izRtvZ1ZW7K7wRJOJN266\njZ8t7Cm6D4RG5kiKh9aZb+Mu+jrtk/+XMZ71nCr6JV9xHEU1R183x57AP5ZfxwurbubWcRNJDJUQ\nfeZi5M6yqH+zscHDFv9YJEnqk8nrzXWjx/Lfi6/ms1OnAxCMWDX0/b6qqsq/9m9jtqmS71w6gwyr\n9jugk2Wun7qMTUXPUzX/BM+uuJEvXzKTL00ejd55EH+yFsSrxjS8mTdhCrnk92Z16S7mVHyOR0q1\nEv09k6by88VX8bdrVrH6ljs58dmv8LdrtK7Og00NfGPtajxBhaClOKYe7VxhyAFWZmYm3/zmN7nn\nnnu44YYbWLlyJVOnTh34D88Sep2MI9kcMRstq23nVG0Hl0/PjfwApSWaaXP5ohqONrV7ImMxBkt2\nui2iyxgqiqpqAVZmArMnZqICWw/1DQb8gSBOt59xoQAo1pDrpjYPlQ1OLpuWg0Ef+2MgSRL3XTMe\nnSzzxFuHODhC+iuABVOyGTXME9vYkOj6WEUbxytbyUqzYjZqPy75DnsPL6yP92oizt5B1IGTzYwv\nSGH2+Az29NK0xEO4vd5s1PHOlvJ+hfWBoMLWQ3VMH+vokUULl/vK66JnK7YcqiPRZmRCQQoFmQl8\n/ZapNLV5+N/XDkQywadq29lxpIElM/PRyRL7jneNkjh8qgVV1RozBsJi0jOhMJVdxxpQVZWqBhcS\nXZqinHQ7Tre/jxAetG7D7HQbhVkJWhZrR2VU0fJQCQQVmtu9cQdYRdkJqCqU10f/HpSGgtCRCLAM\neh13LdPa8/Oi6KYGwpFioaFVu5Bzefy0dHjJy+hfxzVnQiZBReUfbx1kx9EGrpldENPc9LK8AkDm\nP8syo57oTra2oOssBduouPcsSxJ/uOpaVBV+tf2THvcFkmbhKnkYKf9O3r75Dn595dK4ZQDhIGua\nI5M/7dkR9TsVUBRePHqI0SmpWpkrThRV5b53X+fB99/CHyMwC/vzlSSnMDZ14O9Mqlmz7znR2sL3\nP16Loqr40q/GVfwdWmavIZCkWUbUJS2lveQR7HQgJ07q12tMkiQuzy/ke3O0MTlvHD/KrIOLcTr7\ndloGFYWvnSzms6cujXsk3D2TppJhtRFQFCqC2jHqogRYLV4PiWoHn0vejS9tSc87ZQPezBvJbnqe\nJZlmfjBvEWOVw6gqPF5XjNOv/UZ4sm9HDjp7DKEGTd/2hXWbmWBs4P9MyY+6T50sk2rWvu/bamt4\n5vABbn79JRoNo895s9FhGY2uWrWKN998k9WrV/O5z31upPZ02shOs1ET6iT8aHc1Rr3MvEldnQvh\n7FQ0oXtjm4e0RFMkGBsMOWk22l2+YQ3JbWh14/UHyc+wk5VqpTAzIWqAFZ6JNn2MAwkoizFOZu8J\n7eTbW+gcjdREM3cuGUNpZRsvrztOos044AiQM0WS3URmioWjFa0cq2iNmJEC5GfYqW9x4w35mx0u\nbyU9yUx5nTMiwK4POdJPLk5lzsRMAkElrixUd8pqO9DrJG68rISTNe0crWiN+dh9J5pweQI9PncA\neQ4bElAexQup0xNgT2kTs8ZnRMqPY/OTuXvpWA6dauGVkCD9hQ+OYjLoWDm/kHEFyZH3GLQsncWk\nozgnPp3C9DHpNLR6qGp0UdnowpFiiWjTckPeZ9GE7pWNLvJC9y+ZmU9Tu4fdx/oKi8vrOvja/3wc\nEazHS3O7B0VVBzQZDVOUpV0Vl9VED7COV7eTkmAiNdEU9f7BMqkolYfvmsEV03MHfnAvMpIt1Le6\nI0Et0G8GC4j8Hry/tZwEq4Els6KfpEDLinxxfDbPdkxm//E1Pe7bU1/HnGf+zkutBRGTx3jJTUjg\n3klTee7wAU60tXTdIcl8kng/AetoChOTyLQOzjNPkiQ+N3U67T4vlVEsET4sL6O+08Xt4yYNal1Z\nkriyoIh3Tx7na2tXRw1IfvbJBu5957VBXxx8XFXBX/ft5k97doDOSufoH/YY5PzND9/nyt0FOIu+\ngzv/84NaO8tm57DbyFcrZ0Qc7cO8ePAgBz1JPFzsGvQ56ssfvMNtGyoIqDKyp28nYarJzKaiZ7i7\nKBHV0PdCpLP426AGsJz6H0ATuG/35fOD3ZXc9darBBQl4iQv95of+Pvd23AHFP6V9QoZybE/u2Hu\nnTSVJ5atZFd9LT+onqRlsM7RTnG4QJ3cY5GVZqWu2U2nx88nB+uYPSETazd9SNjjqjFKmbCpzTNg\nB2EsckLlgv66qjYfqOXnz+yM2W1YEcpsFIT0RHMmZnKypoO6lp6ZsXBwmJNmJSvN2sN4szv7jjeR\nnmQmKzW+QGnepCymj0nH5QkM2/9qpBmTn8zBU800t3so6ib8zsuwo6IFAhv31SABn79+EhJE2tsP\nntRE2ZOKUynJSSQ9ycyWKIFrf5yq7SDPYWfxtBzsFgPv9nKX787mA3UkWA1M7FWqMxv1ZKRaKY/i\ncbbrWAOBoMLciT2DskXTcrhsWjZvbT7Fu1vK2bC7iitm5JJgNTK1JI3qRheNoRN2OEvXvcOqP8Jl\n813HGqlqcEaCKiBiLtu7TOh0+2lz+sgJlRKnj0knPcnM2p19r7j3nWjC6fZHMkjxEs7wxJvBSkkw\nkWw3cjJGR21pZRujcpNG9PM8Ji+5R3YyXhzJlki3cth3LM/Rf1AiSRJzQp+LlfOKBnzeL89ZgUPn\n4oc7jvbICv1l3y5sepll1tJIe/xg+NqlszHqdPz3tq4s1hvHj7LspWf4454dg14vzI2jx7Hjrs+S\nn9C3w/PZwwdIt1hYUti32WcgHpgyne/PWcDLxw7z0Po1PV6LZo+bJ/bvxqzTx/19CXPPxCksLx7F\n//tkA/sae3ZYHm1u4u2TpSzOL8A95oeaW/wgmJWVw0PjE3mmYyovH9gcuT2oKPx43TomGeu5IW/w\nmdOVo8ZwoKWDv7TN6NNJ6PL7aW/eh959IuZ+FWsx3uzbsVT+Dclbh771Ey5xZPDLy5ewqbqSl48e\nRjFov3eyvyvAqu908ff9e7g1z8B4Y2Pco5lWjRrLfZOm8mS1hSMe24Ddj2eTiyvASrUSCCq89ckp\nvL4giy/pWf9ODWeworT2N7V7Bq2/ChMurcTSraiqypubyjhc3hoze1Je70SWpMiJbvYETYi9tVe5\nK6whS000U5SVEDXA8geCHDzVzNRRaYNK2d9zzXhyHTZmT4juTHy2GBfSYQE9Wu3zQjMNy+s62Liv\nlolFKYzKSWJcQTJbDtahqir7TzaTlmgiK9UaOVkdKmuJGM8OhKqqnKrtoDArAaNBx1WX5rHneBNV\njS4CQYXSqjY+3lvNx3uqWb+nmt3HGpk9PjPqkOKCDHvUDNaWg3WkJ5kpyel7krlzyVgKMxN44cNS\n9DqZZaEMxpRQZnLfiSbqW9w0tXuYXBx/k0VKgoni7ES2H66nvsUd0V8BJNuNWEz6PhmsiFYrlHWR\nZYmZ4zM4Vtnap+we9mgbrBlsOOM1mLE2RVmJUTNYLR1emto9I1IeHAnCWbmGVjeVjS4sJl0f491o\nXHVpHncvn8DlcWTNEixJPJJXybY2mRNtrbR6PGysquDVY0f4dL6RJJ1XM78cJJlWGz+afxk3jtZK\npKvLjvP5999mekYW90wcunTEoNNh0OnwB4O0ebt+l5vcblaXHefmsRMwDKI82J2vz5jNV6fP4h8H\n9vLEvq5B2H/euxOX3883Lp0z6DUlSeJXly8l1Wzhi++/TWe3sT2/370di17PZ6dMH9J+Ab4xbQoL\nzOV855M97G/UzhUvHzvM4aYmfpS6DmK4xvfHypIxLMzJ5wdNV9Hi7FkifP7IASa9+D5l/mR8jhUx\n1+gs+jYoPmwnf4GhfQf+5LncMX4Sk9Md/HL7Zvy6JFRkJF9XNrvT72dhbj7fK2xDRUYxOmKu35tv\nzZyLVSfzVPvUc9qq4aIKsMJlrfe3VZLnsPc5YaUmmJDo6+bu8wdpd/kiGa7BkpZkxqiXY85CPF7V\nTk1TJ7Ik8f626MZplfVOstOsGPTaj0lqoplROYk9ykDQVSJMSTBRmJVIS4eX1l4zy45UtOLzK3GV\nB7uTZDPykwfmMGNs/F+EM8GY0BgdSerK8AGkJ5kxGXWs2VlJU7uHhVO1gHr2hExqmzspq+3g0Klm\nJhV3BZpzJmaiqCrbD8fn/tzQ5qHTG4iUJq+ckYtRL/PrF3bzld+s52f/2sHf3z7M3985zJPvHCYY\nVFg4NfqVWkGmncY2D52erh/l9k4fB8tamDMxuiWGQa/jSzdOJtFm5PrFo0iyayfkrFQrGckW9h5v\nYn+3LN1guGRMOhX1ToKK2qNUJYUC/epewVFVJMDqCsbG5CURCKqc7BbgqKoaCbAqBxlg1be60esk\nku3xl/SKsxOobe7s44F3vGrk9FcjQcQLq8Ud8R2L5wLIbjFw69Vj+9VSdufescUcKfwto20qzxze\nz42vvYgswZey61ElQ2QszWC5f/IlLCkqYW35SR54902mpDt4buVN2I1Db2IB8AeDzH/2SR7dsjFy\nW6LRyF+XreQzk4ZuAyJJEj+Yu5DPT53B5JAx6Z76On61fQsrSkYzIW1oo5PSLBYev+oajrY086c9\nO/AFgyx/+VmePXyAOydMJt0ydHmFZCvmqax/Y5AUTobKsWlmC5ekJ3Kz/VAfs8641pQkfrrocloV\nE//vWNftqqryrwP7mGBqIzd9NIo5doYpaBuNN/tWLBV/RlI8+JPnIUkS3501n7L2Nl48ehjVkIrs\n77JxKUpK5ukVNzJWX4tizAAp/kA53WJl7XVX8pO0tcjncIA1rFmE5xvhTFIgqLD4kpw+P156nUxy\ngqmPm3s44OreEj8YZEkiK80aM4O1fk81JqOOlfMKefmjExyvbmNUL5+i8voOxub17NwrzEpg0/7a\nHh5kLe0e7BYDRoOOotBJv6y2g0tGd52Q9h5vwqCXR0Sofi7gSDKTbDditxojAnfQXvd8h53Sqjas\nJj0zxmo/mJeOc/D0+0d5fs0x3N5gj8xOnsNOrsPGR7urWTglG5Ox/y99uIkg/FonWI2smF/EjsP1\nTB/tYFxBMgVZCehC74/RIMcUIeeHfMgq6p2R92bboXoUVWVOP1lDR7KFX3xxPtlZiRG7C0mSmDIq\njY/3VBNQVBzJ5sjEgXiZPiadV9Zr+q7cXqWqnHQbO47U9/jsVTU4MRt1PfRM4eCltKotMk+ypcNL\nm8uHTpYiWqN4aWh1k55kidtfCrqymmW1HUzoNn2gtKoNg17uEZSfTbqbjVY1OAdtFxI36ZdRUPYz\n2lo2sbx4IWOSU5mY5mDCiS8QtJYM6kTXmw6fl++uX0txUjLPr7w50v02HAw6HXOzc3nu8EFuGD2O\njdWVfHvmXJYXD76U2RtJkvjJwssj//3ckQPIksS3Lp07rHUvzy/kyWuu48qCIow6HZPTHawoGc0D\nUy4Z+I/7QTVmUGjysmduI55cLVs9JyeXj64djbxZ1QKVITAxzcHnM6pY05KCJxCgoqOdN48f40BT\nA390bMDrGHg2Y2fx/8FU8wISCv5k7fVbVlTCA1MuYXxqOkpLWkSD9e9jh7k0M5vCxCRkXy2KKfrM\n2/4ozJgAso6mlhMknKM6rIsqg2W3GLTgo5e4vTtpieY+GaymIVo0dCcn3RZVg+X2Bth6uI45EzK4\nckYeFpOOD7b3dPR2uv00t3vJz+h5Ish1aG7l3UX5zR3eyAmuINOOJPUVuu873sT4gpQhGWqei0iS\nxC2Xj+L2JeP63BcuE86ZlBnJ/iVYjUwsSuVoZRuSBBOKegaa1y0opqrRyc+f3dWvYz5o3ag6WeqR\n4Vk1v4j/vH82dy4dy8zxGWQkW0hLMpOWZI4ZXEFX9i2sw1JVlfV7qinIsEeOIxYGvdzngmHqqDR8\nAYUDJ5vjsmfoTW66DUeyGZ0s9dHq5abbcHkCtHdzSdeyLrYe+0iwGslKtfbQWoWzVzPGOmjp8A6q\n+aNhEBYNYbouNHp+D45XtVGclRC1XHs2MBl1JNmMlFa24fIEhtSJGA/+pEtRZQuG5vUUJyWzpKiE\n3IQEdK7SIZUHuyNJEp+ZNI1Xb7iVZPPQfy9787mp0+kM+Lnu1Rf4/a7t/c4BHA7/Of8yttx5P1Mc\nww9ury0ZHbFL+MXiq/nK9FlY9MP0hJMkgpYiMoMnSQl11tkNRhIVrVw4lAxWmB+PcrJr9L8x6/U8\nsPoNHt26kRlJMp9O2BeXXixoG4Mn5y78CZegmjJC25V4dNGVTM/MQjGk0dzZxn9sWMdX1rzLb3Zo\nY5Rkb+3Q9i0b2KpcwqSPLaw+fuamcAyGc+OX5QwyZ2Im18wp6CFu705qoqlPgNUYyWAN/QcjO81G\nU7u3z3DfrYfq8PkVFk3TzC8XTc1h++H6Hn5cYS+n/F5X2tG6uZrbPaQmaPs0G/XkpNl66LDqmjup\na3EPujx4rjN/cjaLZ+T1uT18cl3Uqyw3Z6L2A1CSndjHCHPW+Ay+fOMUKuqdPPrUThrbYne6hQXu\n8ZZn+iPZbiLRZow0NByvbqei3snlMwbfkQaaNs0Y2tdgy4Og/TgumZnPnIl9NWPhjNaxUMekqqqa\nb1MUUfbovCRKq9oiQuIT1e3odRLzJmlXrVVxlglVVaWhzR13B2GYBKuR9CRzDx2WPxCkrLZj2DYh\nI40j2cKhkBt+91LriCKb8CfPxdiyvus2VUHnPjEkgXt37AYjX54+kzTL0LL9sZjqyOSbl87hu7Pm\nsfPuz5JtPz2u3SadnsLEc+sz0ZugpajvuByPJvQeagYLwGbLwuKvAlXll5cvYftdD7B5/BqsiYUE\nbWMGXgBwTvwfWmf3HZ1T7exgyv7LGL1nAX/Zt4vbx03kR/M030ydd2gZLIApqYn8qXAXV5f0nQxw\nLnDRBVh3LhnLDYtivxlpSWaa2709Wneb2jzo5MHpPnqTEypP9tZhrd9TQ67DRkmojHHVpXkoqsqH\nu7o6ryIBVq9RNjmRAKvrBNXc7u1RogkL3cMnt7Bma8oFFmDFYv7kLP7j3pmRdv0w08c4sJr0TI+h\nJ5sx1sG3b5tGm8vH/31yO0+8dZBPDtT28H7qEriPXKahIMMe8Wz6cGcVZqOuT/dgvBgNOsYXpmhZ\nuiEO5r56Zj6fXdl3vMW4gmTSk8wR36/2Tj9Ot5+cKLYCY3KTcLr9kWHrJ6rbKMhMiOjWKuMsEzrd\nftzeII7kwV/oFGUlcLJbJrestoOgop4z+qswjmQLgaD2Xc0ZoINwOPjSl6B3HkTnKgVA9lQiKd5h\nB1ink4fnLOA7s+aNaGbsfCRoLdYCrO5lMXctij4pqgt7vCjmbCTFi+RvZlZWDoWWIIaWDfjiKA9G\nkHR9BmUDHG1p5pjbxOXWStbddje/umKp9j6qQSRfI4pxaL9xkq2Eu8wfox9kt+eZ4tzc1VkkPdFM\nUFFpc3adSJvaPKQkmAal++hN2Kqhuw6rot7JyZp2LpvapQdzJFuYPsbBul1VEVfviroOkmxGknqZ\nnNotBpLtxoiOxe0N0OkN9BiaXJSdSLvLx+HyVirrnew80hARQF8M6HUyxVGG+FpMen7+xXlcMzu2\noHdcQQoP3zWD8QXJ7D7WyJ/fOMi3f7+RvSEDz6Y2Dy5PgMKsoQ0JjkZ+pp2qBhdtTi/bDtczb3JW\nD13ZYLlxUQmfWT4hZsZ2qOhkmWvnFnKypp1Dp1oigvdYGSyAY5VtBBWFsroOSrITSbYbsZn1Pdz2\n+yNi0TCIDsIwRdmJNLZ5cLr9KKrKGxvLMOjlSIPEuUI4eEy0GYc14WAgvJk3oiJhqn0JQDMYhWGX\nCAWnn6ClCCnoQvJ385fz1A4rewV93dxN9W8iqUG8GbG7B+Pl8vxCKq9w8WbOvxif0pVNl30NSChD\nzmAFLSXIgVbwNg/84LOACLB6EdZZdS8TNrYP3QMrjCPZgk6WemSw1u+p1kolk3t+uFbMK8QfUPjh\nE1vYfrhec3CPocHJddgjAVZjqIU9tVtrd7hT8hfP7uKHf9vKkYpWpo2+OLJXA2E1GwYMmvMcdr50\n4xT+52uL+I97Z5KdZuVvbx2k3eWLlF6LskauXFGQkUBQUXnhw+MEggpXXDK08mCYwqyEmF2Lw2XB\nlCyS7Ebe3FRGZZQOwjBZqVbsFgOllW1UNbjw+RVKchKRJIn8DHvcJcL6Vu27M1gNFmizHkHTYa3Z\nUcn+k83cfuVo7JaRDTyHS9h+4rSVB0Mo5lz8KQsw1b0EqtotwDp3M1gCDcVSBNBzTIx76GW2yLom\nrcta9taAqmA59XsC9skEEi8d1rphEq1pSGoQKdClx5S9daHnHloGK2gNVaOcQoN1XhDO/nTvJGxq\nG7oHVhi9TiYztauTsNXp5eM91cyZkNnnR744O5EffWYWjmQLf3h1P+X9BVgh8byiqBGPoB4ZrKwE\nvn37JXzphsl86YbJfPnGKVy3YPDGfBc7sixRnJ3Ig6sm0ekN8uQ7hzlV14FOlgY0gxwMYaH75gO1\njM5LGlDcfjYx6HVcM7uAw+WtbNxXg82s75NlBU3LNTo3iWNVbZwIlemKQ4F/rsNOZaMrrvEeNY2h\nAGsI3bzhcuTGfbW8+OFxpo1Ki8s36kyTkaxluqNlAkcab9Yt6F1H0Tn3oes8jqqzDfskLTj9BC3a\n73cPHdYIZLDC773OW4Ox8T30rkN0Fn2t33E+g1rfqF3Yd3dzD5uEDrVEGLSGzmUdIsA6Lwh7XYUz\nWG5vgNYO75A9sLqTk2aNdBK+uamMoKKyamH0YCc7zcb3776UVfOLkCUppoYmN92GL6DQ0OaOZLC6\nmxNKksSkolRmjs9g5vgMLh3nGJLLtEAjL8POLZePYndpI2t3asPCw92JI0FmijUiTB9wr/hFAAAQ\nr0lEQVRu9upMsPgSzb2+vM7Zp4OwO2Pykqhr7mRvaRN2iyFSos5z2PD6gn2sUXrT7vKxdmclEwpT\nBrTOiIbVbCAzxcKWg3VYTTo+c+2Ec2oaQZjsdCsmo45x+affQsWbcT2qpMdc+xI6VykB66gRO5kK\nTh/BkE9ZjwDLPcROvG6EndRlTzWWU78laM7Dm3nzsNbssb5BC7Ckbm7usq8+9NxDDLBC2TyRwTpP\nsJj02Mz6SIC1dmclKjB11NBM57qTnWajvtVNTZOLj3ZXs2hqdr9aKL1O5sbLSvjTdxYzuSR6WS83\n1Mpd1aCNRZEgLvdnwdC5emYeE4tScHuDFIxgeRC0TFl+hh27xcDM8eeWoWs0zEY9V8/Uujdz+7EV\nCOuw9pQ2UpydGAluwhm6ygF0WC+uK8XjC3LnkrFD3mtYi3f/iolDGtp+JrCZDfz2a4sinm2nE9WY\nhi/tSky1L6PvPCbKg+cLOgsBSwmG5lAXaNAFgY4hZ4EiyEYUQzrGhncwtmzAXfAlkEeuhK4atc/0\nSGaw0FnxJc8H47mlpQwjAqwopCaaaWrz4PYGWL21giklaVHHlAyWnHQbqgp/e+sQkiSxcn5RXH/X\nn09PWDxf1eCksdVNos14zvj6XKjIksQDKyaSlWpl2ggE3r359JKxfPnGySOaGTudXH1pHjnptn5H\n8RRlJaDXSahozuphwlqj7o7uQUXpMRvuaEUrG/fVsnR2fqRzdiisWlDEl26YfM5blETzNDtdeLNu\nQeepQOcuEwL38whP7j0YW9ajcx5C9oazQMP37lJM2Rg6dqHok/Dk3jvs9XqsHcpgyT0yWHUo+mTQ\nDb1C1DbrXRj75WHv73QgakVRSEs009DmZu3OSpxuP9ctLBqRdcOjeo5Xt7NkZn4PrdRQMRv1pCeZ\nqWp04Q+qPSwaBKePlAQTP3tweG7PsYjW9XguYzUb+Oln+5/bZtDrKMpKpLSqjZJuUwrMRj2OZHPE\nqqHd5eOn/9yOQS9zzewCZk/I5F/vHSE10cR184enHcxOs0WmOQg0fI4VqLIZSfGIDNZ5hCf3Xmwn\nHsVS8Wc82bcDw8gCdSNozkbv3Icn7wFU/chm58MarO7zCGVv3bBLm+cyItURhbQkM42tnkj2qvfY\nmqGiDRQGk0HHinmFI7ImaFmAqkYXjW3uiMmoQHCuMTY/GUmiTzY4z2GnssFJUFH402v7Q2N0ZP7+\nzmG+8bsNVDW4uOOqsUPSXgn6R9Un4HUsB4RFw/mEakzDk/UpzDXPoXcdBYbn4h5GMeejSkbcBV8Y\n9lp9kK2osrlvBmsEAsNzFZHBikJaohmvP4jXHxyx7BVoxo+zxmcwKidpRDUguQ47+082o9fLjDvH\nfH0EgjDL5xYwuTi1T9dsnsPO7tJGnvuglMPlrTywYgLzJ2dx4GQzq7eWk5JgPiOapIsVd8EX0Xkq\nCCRMOttbEQwCT/6DWKqfwnLqf4CRyWB1Fn8XT/Ydp6ebVJJQjOk9AyxvLf6kWSP/XOcIIsCKQtiS\nYSSzV2G+cP3kEV0PtJbuoKIS9AVFBktwzmIzGxgfpRs2L8OOqsKanZVcMSOXBVO0bqbJJWkxmzsE\nI0cgeW7U8SaCc5tA4iX4k+ZgaNsCkoxqHP53RTFno5hPj28eaDqsSIlQVZG99Rd0BkuUCKNQnJ1A\nRrKFmy47N+cb9aa7KaHQYAnON8I+YqNyE7njqvhmngkEAnDnP6j9w5Shjak5x1ENqZEMlhTsQFI6\nL2jvNZHBikJ6koX/+sK8s72NuMlO07RdqsqICOcFgjNJVqqVB1ZMYEpJmuiAFQgGgTfzeoJHv4/O\ncn4EKYoxHUNbGdDdxX343Y/nKiLAugAw6HVkplipbe7sMSZHIDgfkCQpUhYUCASDQDbSMeUJkhPP\nTV+33iiGtIjRaCTAMp4fweFQEJeLFwi5DhuyLJFsFwGWQCAQXCz4Uy+D7CVnextxoRrTkAPtoPiQ\nfcObQ3g+IDJYFwiLpuZQlJM04PBigUAgEAjOBooh5Obub+5ycRcBluBcZ+qoNK6aW0RDQ8fZ3opA\nIBAIBH3objYq++pRJSOq/vTP3TxbiBKhQCAQCASC047abVyO7A0NqL6AB4yLAEsgEAgEAsFpJ5zB\nkn1NIRf3C7eDEESAJRAIBAKB4AwQ1mBJ/sbQHMILt4MQRIAlEAgEAoHgDKAaNL2V7GvSAqwL2MUd\nRIAlEAgEAoHgTCAbUPTJyN46ZH/jBd1BCCLAEggEAoFAcIZQjGnoXYe0f4sASyAQCAQCgWD4qIY0\ndM5QgHUBu7iDCLAEAoFAIBCcIRRDGnKgVfv3BTyHEESAJRAIBAKB4AyhGNO7/i26CAUCgUAgEAiG\njxrywgKED5ZAIBAIBALBSKCE3NwVQyrIxrO8m9OLCLAEAoFAIBCcESIB1gXugQUiwBIIBAKBQHCG\nCJcIL3T9FYgASyAQCAQCwRkiksG6wDsIQQRYAoFAIBAIzhDhgc8XugcWiABLIBAIBALBGUIxZqLq\nbARtY872Vk47+rO9AYFAIBAIBBcJejvNC3ahGNIHfux5jgiwBAKBQCAQnDEuBoE7jECJ8De/+Q2P\nP/74SOxFIBAIBAKB4IJgyAFWR0cH3//+9/n73/8+kvsRCAQCgUAgOO8ZcoC1Zs0aioqK+MxnPjOS\n+xEIBAKBQCA47xlygHXDDTfw4IMPotPpRnI/AoFAIBAIBOc9A4rc33nnHR599NEet5WUlPDkk08O\n64nT0uzD+vtYOBwJp2Xd8wVx/OL4L2Yu5uO/mI8dxPGL4z/3jn/AAGv58uUsX758xJ+4qcmJoqgj\nuqbDkUBDQ8eIrnk+IY5fHL84/ovz+C/mYwdx/OL4T+/xy7I0pKSQMBoVCAQCgUAgGGFEgCUQCAQC\ngUAwwgzbaPSrX/3qSOxDIBAIBAKB4IJBZLAEAoFAIBAIRhgRYAkEAoFAIBCMMGdtFqEsS+fVuucL\n4vjF8V/MXMzHfzEfO4jjF8d/+o5/qGtLqqqOrFeCQCAQCAQCwUWOKBEKBAKBQCAQjDAiwBIIBAKB\nQCAYYUSAJRAIBAKBQDDCiABLIBAIBAKBYIQRAZZAIBAIBALBCCMCLIFAIBAIBIIRRgRYAoFAIBAI\nBCOMCLAEAoFAIBAIRhgRYAkEAoFAIBCMMBdMgPXGG29w7bXXsnTpUp5++umzvZ3Tzu9+9ztWrFjB\nihUr+PnPfw7Apk2bWLVqFUuXLuXXv/71Wd7hmeGxxx7je9/7HgCHDh3ipptuYtmyZTzyyCMEAoGz\nvLvTx9q1a7nppptYvnw5P/3pT4GL6/1/7bXXIp//xx57DLjw33+n08nKlSuprKwEYr/fF+rr0Pv4\nn3/+eVauXMmqVat4+OGH8fl8wMVz/GGeeuop7r777sh/V1dXc+edd3LNNdfwxS9+EZfLdaa3elro\nffy7du3i1ltvZcWKFXzrW986N99/9QKgtrZWveKKK9SWlhbV5XKpq1atUo8dO3a2t3Xa2Lhxo3rb\nbbepXq9X9fl86j333KO+8cYb6uLFi9Xy8nLV7/er999/v7pu3bqzvdXTyqZNm9Q5c+aoDz30kKqq\nqrpixQp1165dqqqq6sMPP6w+/fTTZ3N7p43y8nJ14cKFak1Njerz+dQ77rhDXbdu3UXz/nd2dqqz\nZs1Sm5qaVL/fr95yyy3qxo0bL+j3f/fu3erKlSvVSZMmqRUVFarb7Y75fl+Ir0Pv4z9x4oS6ZMkS\ntaOjQ1UURf3ud7+r/v/27S+k6e+P4/hzuSmKF1HOHEuCwjCslOifaf8kUZMQXBcVZmAiQuRaFzVC\nFKKalGUXQRDIbuqivyQMlYK80ClU3gyyYFSOqLEc9kdx2fz4+V7Ib2B/flezyefzflztnA12Xuf9\nOZ8dzja3262qqj7y/4/f71d37typ1tTUxPoaGhpUj8ejqqqq3rhxQ718+fI/H2+8/Zp/YmJCLSoq\nUl+/fq2qqqo6HI5YnRdT/TVxgjU4OMj27dtZunQpaWlplJWV0dvbm+hhLRiz2YzT6SQ5ORmTycSa\nNWsYHR1l1apVZGdnYzQaOXDggKbn4OvXr3R0dNDY2AjAx48f+fHjBwUFBQBUV1drNv/Tp0/Zv38/\nWVlZmEwmOjo6SE1N1U39FUVhdnaWSCTCzMwMMzMzGI1GTdf/3r17tLa2kpmZCYDP5/tjvbW6Dn7N\nn5ycTGtrK+np6RgMBtauXcunT590kx/g58+ftLS00NTUFOuLRqO8ePGCsrIyQLv5vV4vBQUF5Obm\nAtDc3Expaemiq78xYe8cR58/f8ZsNsfamZmZ+Hy+BI5oYeXk5MQej46O0tPTQ01NzW9zEAqFEjG8\nf6KlpQWHw0EwGAR+vwbMZrNm8wcCAUwmE42NjQSDQfbs2UNOTo5u6p+eno7dbqeiooLU1FS2bNmC\nyWTSdP0vXrw4r/2ne14oFNLsOvg1v9VqxWq1AjA+Ps6dO3dwuVy6yQ9w9epVbDYbK1eujPV9+fKF\n9PR0jMa5j3at5g8EAqSlpeFwOHj37h2bNm3C6XQyMjKyqOqviROs2dlZDAZDrK2q6ry2Vvn9furq\n6jhz5gzZ2dm6mYP79+9jsVgoLCyM9enpGlAUhaGhIS5dusTdu3fx+Xx8+PBBN/nfvHnDw4cP6evr\no7+/nyVLluD1enWTH/5+vetpHQCEQiGOHTuGzWZj27Ztusnv9XoJBoPYbLZ5/X/Kq8X8iqIwMDDA\n6dOnefToEZFIhFu3bi26+mviBCsrK4uXL1/G2mNjY/OOUrVoeHiYpqYmzp07R2VlJc+fP2dsbCz2\nvJbnoLu7m7GxMaqqqvj27RtTU1MYDIZ5+cPhsGbzZ2RkUFhYyLJlywDYt28fvb29JCUlxV6j5foP\nDAxQWFjI8uXLgbmvATo7O3VTf5i75/1pvf/ar+V5ePv2LfX19Rw9epS6ujrg93nRan6Px4Pf76eq\nqoqpqSnC4TCnTp3iypUrTExMoCgKSUlJmr0PZGRkkJ+fT3Z2NgAVFRXcvn2b6urqRVV/TZxg7dix\ng6GhIcbHx4lEIjx58oRdu3YlelgLJhgMcuLECdrb26msrAQgPz+f9+/fEwgEUBQFj8ej2Tlwu914\nPB66urpoamqipKQEl8tFSkoKw8PDwNy/zLSaf+/evQwMDPD9+3cURaG/v5/y8nLd1D83N5fBwUGm\npqZQVZVnz56xdetW3dQf/r7erVarLuZhcnKS48ePY7fbY5srQDf5XS4XPT09dHV1ceHCBdavX8/1\n69cxmUxs3ryZ7u5uAB4/fqzJ/MXFxbx69Sr2E5G+vj7y8vIWXf01cYK1YsUKHA4HtbW1RKNRDh48\nyMaNGxM9rAXT2dnJ9PQ0bW1tsb5Dhw7R1tbGyZMnmZ6eZvfu3ZSXlydwlP9ee3s7zc3NTE5OkpeX\nR21tbaKHtCDy8/Opr6/nyJEjRKNRioqKOHz4MKtXr9ZF/YuLixkZGaG6uhqTycSGDRtoaGigtLRU\nF/UHSElJ+et618M6ePDgAeFwGLfbjdvtBqCkpAS73a6L/P9Pa2srTqeTmzdvYrFYuHbtWqKHFHcW\ni4Xz58/T2NjI9PQ069at4+zZs8Diuv4NqqqqCXt3IYQQQggN0sRXhEIIIYQQi4lssIQQQggh4kw2\nWEIIIYQQcSYbLCGEEEKIOJMNlhBCCCFEnMkGSwghhBAizmSDJYQQQggRZ7LBEkIIIYSIs/8AGSGL\nUSnExRQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2fa89c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict_and_plot(encoder_input_data, decoder_target_data, \n",
    "                 sample_ind=6007, enc_tail_len=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GPcOMGa+i0+nw8fHhxRdfcbkeJaVRSl2fh3TJkiVLyMrKcma9vvjiC/bv38+0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\nWD86wPRizukpa0S305pgDXHkZK3mMaYWcsTCvrb7EltlptVjsigAJ9p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BKAh8+IbtQHcx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crde9v7+Nsbbml6PqWJ0DcQlemaGI2TmRRrIiUnShQErl67nsdPHGsZ12EEJpDkSTA0pNwbFRln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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2f826128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict_and_plot(encoder_input_data, decoder_target_data, \n",
    "                 sample_ind=70450, enc_tail_len=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9rnlXhZycHEaMGMHgwYPp1KkTf/vb3/jqq6/c8y36WtFoNMXWUXT9iqLw3HPP0aNHDwBy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\nfb+wssJkD8r0wYK/Pjk5jCl7QfHjUhTOa2zmoaOHiWtW1IbprEx9Ly1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LxWtDA/RGIhiu\nuqWVI80kkqln3PFouBa7bHK8F+foE4uudU68CIAjuhu0KJIxgym5yurKHg9KvjvDMOb9hTBNc96f\n/X4/P/jBbD37E5/4BF/+8pf5whe+UPB7VFcXnohcDLW1JVraJwG+oen0/w9W+KitWvyDvZK//kJY\n7V9/OOxL/+9q/F6sxq95Lqv265/YzEORZva+/QxfvPT9i55+ta+PuCFzfmiq4O/R9oTVYD8lq1S3\nbAJHkKB+hGCm1090c0it4oqmQM7zL9rQwYeHthKu9FFbVfh/q9f6+7nqF3fz8w9/mBu2bp333BmG\nNSgxTiL311Z3GvTfQ22FDq4wpIJyK5vWgS/IfT2HGE/E+dJFF/DMT3/KU8PHOK2qHXomqK1yglLC\npoREEgB/RTX+hfdW0QpTL86/55e+DYf/BW4YAldqyjQxBjMHoe4SpKEnqZXeBpcGTv+81y7Hn/2S\nRVhDQwOvvPJK+s/Dw8PU1c02Y/b19fHcc89x4403ApZIcziKe7vR0Wi6dFIuamuDDA+XlsB7MjAy\nNivCBoemkBesxljpX38+xNc/+/VPR+Or7nsh/vuv3q+/NrSJB2fW84NnXuOWrRchL3DVfrff6nE6\nMxAr+HsU0K3PtN3H+jm3spGKwHakwReYyPB6degwvVqIFl8g5/ltziDfvfRq0Cnqv9UrnT0A1Mie\nRa8LGy4evPlm2l2hnGe6pLVUAONdr6CFz8U30oUfGI54YTrCE4c6CbvdnFvZyD3XXs95Tc1EBl8h\nCIz2HsLwthd8vzZybJBqIBJTiC+4N59RhT8xwvDgKMjWAvbwyJs4TY2p/b8i0fhh676HH6MCmGz8\nHKGhp5k5+ihyfAKX5GMsdebx/tmXZakk46jkcuT555/P888/z9jYGLFYjIcffpiLL744/bzH4+Eb\n3/gGx44dwzRNfvzjH/Pe97631LcTFEhSnRVdoidMkIn0dKRY4C1YTYQ2sc01yIxucHRqYtHTrwz0\n0+iM0+It3Cyo9fr45LbT2FxlLdjWwufiiLyZDgqdS/e41dvUUUD8BZBxt2QuDk9Y+xszZZx5HA6u\nWr+eam/uuAYtsAUAR/RtIBVP4axKC6BXBvo5o74RWZK4rK0Dr8M5J0qitJJkrgb6RYGtpokStXrW\nXCMPpK9zTL6IKSkkqy9BC56Kc+KF1MTl8u4HgyWIsPr6er7whS9w66238sEPfpBrr72W7du38+lP\nf5o9e/ZQVVXFHXfcwec+9zmuvvpqTNPktttuK+e9CzIwNx9MiDBBJnTREyZYjXgaOMVnVQr2jS6e\nkOyLRjjXNwTOwktWkiTxNxe9Jx05oYbPRTI1nFOvL7o2aE7wl5VPs71hTd5zP/Cre/jkw78t+D7A\nEmEtgSBehzPj8892d3PvoTwTkp42TMWfFjpycijdDxZNJtk/NsKZ9VZ8h6rr/N3Lz3PvoJy6tlQR\nFgWsUNUDY6PpyA+YGwZrCVgpOYSsTWDKXlwjvwPD6n9zTr6MFtgGit8SwpMvI2tTJ4UIW1LH2q5d\nu9i1a9e8x+b2gV111VVcddVVS3kLQZGo6uwPcFKIMEEG0tORIjFfsJqQJDaHK5Aw2Tc6Mi9LC+Dh\n03pxHLiTZPU3ijrWME26pybpqAijVpwDgGPiBdTKC+Zd1+EY5Ws1jzFSk79kF/Z4ODq52K3LxZHJ\ncdaGsyfx//Nrr/HIocNctz5z+j0Akozm35SekJQTg2khlNB1Pn/6WVze1gGAQ5b5+YF9vOT3cKt/\n6cn2b0dlLnzgR/zFOefzn886D5i7FslywhwpcRhvvgXvsX/GOfE8avh8HJOvkmj6GABqeCfeYz/A\nMfkKesrZW86IesQKQzhhgnyInDDBasUTWsta19SiyUPn6OP4D90BjR8g3vKJos78l92vc86Pf8jw\nzAymqxrNvzE9qTeXvqlxJuUGkJS8Z64JhTk6OYFRROD2/zj/Er6YEi+ZWFdZSf90lLim5TxHC2xN\nix3LCbPKjdVeL1/ZeTFnpJwwSZJ4/9oNPDMwxKjuXUI50nLCHh6wxNhDRw+nn5stR1oCT5m2Jjdn\n2j6HKbtxDf8HyvTbyHo0LYDV8E7rNdrESeGECRG2whA9YYJ86GJtkWCVovs28mbrd/jWReenH5Nj\n3fzwiW/ze8MfZ2rLP0CRfy82VFqrmg6MjwKgVpyLc/JFMOf//v3DfUGuOnZjQWeuqQgT13UGpqMF\n38d5TS2c15Q9g2xtZSUm0D2VL6ZiK3JyCCk5Os8JOzQ+tkjAXd7WgWYYvKhtXUI50hJfv+uz7uui\n5tltAoarFhMp7bI5ovsxHGEM71qSlRfjHn4A54SVD6aGz7Ve42lG91hnLPe9kSBE2IpjXlhrkY2d\ngtWBWOAtWK1o/g34ZRXHTGq7i6kT2n0L90c62CdvRyqiH8xmc1U1APvHLBGmhc9DVsdRZuZvkDkS\nc7LeuzjDKxN2c31ngSXJ3kiE+48cJJpMZr1mXaVVqjyaR4Rp/s0AOCdfQjJiGK56TNPkA7++hz9/\n6tF517bb+WNmy5LKkaYJ22uq+eoFl/Lfdl40+6TsxHRWp102ZXo/emAzSBLJ2mtQYp14+u7CcNVh\neGbLvLYgW+57I0GIsBWHSMwX5MMQ5UjBKkX3bWBfsobbHnuePSNDuAd/jTz5Bi8l2zmjqaOkMxv8\nAYIu16wTlhIAzokX0tckdI3upIe1BRozm6uq+eyOM6nxFlZOe7Kni9sevI+RWPa9mOuqLMcuX6+Z\nHrAyxpyjjwNWWn7X1CQjsVi6FGnT4PfT5A+gKqF031axSHoUSYI7dp7PZ3acgW4YDM3MRi0Z7gbL\nZTNNHNP70PxWn1ey9mrrPqdes0qRcxxMuyRpysvfCVveUbKCoklqBpJk7ZAVIkyQCT21U9QhIioE\nqwzdt46wHOfRwRkGn36cJ+q/zW7lbKKamZ76KxZJkthUWc2BlBOm+zZgOCtxTLwIzbcC0D01hYnE\nmkBh65Dq/QHuuOCSgu/h8MQ4TlmmNRjKek2tz8fTN32c9lDuvZiGuxHDUYFr7Enrz656Xh3sB1j0\nPVJkmTc+/hkCb/0R8miJq4v0GQ4nK/FLXhTgI7/9JQlN47fX35S6H2t1kZQcRlbH0QPWYIHhaUYN\nnoYz8kZa+NqkRZjoCRO826iagS+1FkOIMEEmRGO+YNWieKgL1vDtdcd4ob+Xv+2u5mmvNVV3Voki\nDOBPzzyHz59+lvUHSbL6wuY4YZ0T1iLstaHCy51xTaO/wNVFhyfGWVMRzpn9J0kSm6qq8eQLTZck\n9MCW9ISk4bZEmM/hTJdeF2K5VUNgFt8CY2rT7Oz5FF965hkAzqhr4NXBfiLJxOzZicH0/djlUph1\nw+ymfBs9sAU1dCZaaEfR9/NuI0TYCkPVdPweZ+r/CxEmWIzICROsZjTfBm71v8zN1T3cMXYJryZb\nubC5NWPIaaFc1bGOK9rXpv+shs/DMXMQKWm5Y1sDEt+tvZ/1lZlFTCY+9dBvuem3vyro2nzxFDaP\ndXfy7VdfynudXfIDywl7Z3yMLdXVGd3z/7vndT74egjJ1JHUsYLudy6vjScY1v1cmMpau6S1Dd00\neba3J/3+cnIwHSCrz7m3WOtniK7/a7TwfBGGJDNx7uMkGj9a9P282wgRtsJQNQOPW0FCiDBBZgwh\nwgSrGN2/AUd0D98L30mH38GxSIRfXvfhJS0Hj2saz/f1pJ0rze4Lm7QET4c7xh+FXybor8t6xkLW\nhivpnBzPG1OhGwadkxOsL0CEPdXTzd+98nzeM+3kfFNyYDor+S9n7+Qvzrkg47WjsRiPDhskTaWk\n5vwHhmVkDC5rtRrrz25owudw8GRPF2A5cZKp4Rx/HsNRkY6tADBdNcTW/Fne2I9fHtzPvuHhou/t\n3UCIsBVGUjNwORScDnleZphAYCOcMMFqRvdZIa0+bzV3f+Bj/OvVH1jymaOxGNf9+mc8dPQIAGro\nDEzJgXPiRRK6xj0HDjCmezFcha0sAthQWUlc1+mJTOW8TpYknvjorXzy1NPzntkRCpPQdfqjuaMv\n7JBTw1UHksy5jc1c0po5ZLYtVIEJHFNDJYmwh0Y87PQNU+mxJhndioOdTS08ecwSYXpKdDnHn0L3\nby46QmRGVbn90Qf50ZtvFn1v7waiMX+FoWoGTodsiTDhhAkyYEdUiJ4wwWrEFhix9ttZW1lfljOb\nAgH8TifvpCYkUbxowR24+3/CK9NtfO6lCVqbWtjprCn4zPVha5rx0MQYbTma6SVJYl0BLhhAR6rk\nenRqguZg9v40LTUhabjqGZ6Z4eWBPi5obqHC7Vl0bUvqnKNamNpkcROSA9NR3pj28rXG+XEef3LG\nOcQ0DdM0MVypwFZ1jERgc6ZjchLTNG47dQe7Nm4s+rXvBsIJW2HMF2EiJ0ywmNm1ReKvv2D1oYZ3\nMnnaPcRaP1u2MxdOSAJMb/waprOKx99+EI+kcpn3KIarcBFmC6tD4+M5r3uu9xg/2P1aQbmQHSkx\nly+mwnTVYjirMdy1vDTQyx88+JusmWUtAWsis0sNF+2EVXm83L/5DW6qHZ33+M6mFt7T1oEkSRju\n2RKu7i9ehFV7vXz1wsu4oK0t/8UnAPFbeIWR1HThhAlyoolypGA1I0kka98HcnkLQZuqqtOBrQBq\n5fmMnfssv1Ev5rKKKM6qszAdueMh5lLr9fG1Cy/lwpbWnNfdd+Qgf/PicwVFzrQEQzhkmYE5OVzZ\niG76G2Ltt3MkJb7WVmR225oCQU6vq8fjcBQtwlyKwnsDPbT4Ft/7k8e6eKa3e14PmFaCE/bO2Cia\nsXw/C4UIW2GomoHLIeN0KEKECTIiGvMFgvKzsbKa4dgMY/FY+rFDkxMcnU5y6fYbmTjz5Bv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0CY4zCaTGTc/sFQCCt8MqzxtCCswObd6RY3NgEADo0O533MvqEQWlzuabNxt4qCsDqSXo4ElJJk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\nQgghNUBBGCGEEEJIDfx/pWUqiS2vHyIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a2fcd10b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict_and_plot(encoder_input_data, decoder_target_data, \n",
    "                 sample_ind=16551, enc_tail_len=100)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
